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Staff Forward Deployed Engineer
Afresh · San Francisco, CA
Pay
$169k–273k
Setting
On-site
Back to jobs
Staff Forward Deployed Engineer
San Francisco, CA
Apply
Afresh, the AI platform for grocery, began by tackling the most complex problem in the industry: fresh, and has evolved into the core AI platform for grocers.
By leveraging proprietary AI designed for high-volatility environments, we empower partners like Albertsons, Meijer, and Wakefern to drive smarter decisions across their entire enterprise.
Following record-breaking 70% revenue growth in 2025, we have scaled to 6 enterprise-grade solutions, with solutions live in over 10% of the U.S. grocery market. Our platform now orchestrates billions of decisions from the store floor to the distribution center and prevented over 200 million pounds of food waste last year alone.
If you're looking for a role where your work directly translates into massive scale and social good, and you want to be part of the team that defines how the world eats, there is no better time to join us.
About the Role
Most companies make you choose: build the platform, or go deploy it. Here you do both — and that's the point.
As a Forward Deployed AI Engineer, you're part of a single team that both delivers Afresh's AI into enterprise grocery customers and builds the platform that makes that delivery fast. You'll spend dedicated time in the field — embedded with a customer, integrating into their data, shipping AI systems on top of it — and dedicated time on the platform, turning what you just learned into reusable tooling the whole team deploys next. You build the house you live in.
Afresh leads the customer relationship and direction; you and a small team bring the technical firepower — scope and architect the work with the customer, then build it. Because you also own the platform underneath, the rough edges you hit in the field become the things you fix at the root.
This is senior, hands-on, 0-to-1 work in a space with no playbook.
What You'll Do
In the field (forward deployed)
Partner with Afresh's account lead and the customer's technical teams to scope and architect the work — the data sources, the architecture, and the path to production.
Embed with the customer's data and engineering teams (remote and on-site); integrate into their cloud and data platform; build production-grade pipelines and model messy enterprise data into trustworthy data products.
Design and ship LLM- and agent-powered systems on that data — retrieval, agentic workflows, data-quality and analytics agents — reliable enough to run in production, not just to demo.
On the platform (building the house you live in)
Harden what works in the field into the shared platform: the knowledge and grounding layer (knowledge graph, ontology, and retrieval) that makes grocery data usable by LLMs, the agent frameworks, and the serving infrastructure.
Build the evals, tracing, and tooling that let the team measure quality — accuracy, hallucination rate, latency, cost — and ship faster on the next customer.
Build for leverage: clean interfaces and reusable building blocks, not one-off per-customer code.
Across both
Own the flywheel: field learnings flow straight into the platform, and platform improvements show up at the next customer.
What Makes You a Great Fit
We encourage all highly-qualified candidates to apply, even if they do not fulfill all the listed criteria.
5+ years building production software and data systems, with strong, production-grade code
An architect's instinct: you can take an ambiguous problem and a messy data landscape, design a clean and workable solution, and then build it.
Genuine AI/LLM depth — you've built real systems with LLMs and agents (retrieval/RAG, tool-use) and you evaluate quality rather than eyeball it.
Real data-engineering depth: building and operating data pipelines, modeling messy enterprise data, and working in a modern cloud data platform (Databricks, BigQuery, Snowflake, or similar).
Range across both modes — you genuinely like being in front of customers and going heads-down to build reusable infrastructure, and you can switch between them without one suffering. This is the role's defining trait.
Customer-facing comfort: you work well with a customer's engineers and data teams — running working sessions, explaining your thinking, and earning trust through what you deliver.
A bias toward ownership and momentum, and comfort traveling to customer sites regularly (~10-20%).
Nice to Have
Experience in grocery, retail, or supply chain data domains.
Knowledge graphs, ontologies, or semantic layers in production; graph and vector stores (pgvector, Pinecone, Weaviate) and hybrid search.
MCP or similar tool/context protocols; agent frameworks (e.g., LangGraph); MLOps, model serving, and observability for LLM systems.
Prior forward-deployed, solutions, or implementation engineering — or early-stage startup experience navigating rapid customer expansion.
Why Afresh?
We're a mission-driven company that eliminates hundreds of millions of pounds of food waste in grocery stores every year — your work has direct, visible impact.
You'll do both halves of the job: deploy with customers and build the platform you deploy — never a body-shop consultant, never an ivory-tower platform engineer.
Be part of an engineering culture that's genuinely AI-forward — we want to be on the bleeding edge of agentic development, not watching from the sidelines.
Senior team, high trust, and real ownership at a pivotal inflection point for how Afresh scales.
Collaborative, supportive environment & awesome people
This is a hybrid role based in the San Francisco office (3 days/week)
This position is not eligible for company sponsorship.
Salary Band in U.S. (USD): $168,912-$253,368 + meaningful early-stage equity + benefits
Why You’ll Love Working at Afresh
At Afresh, our mission to eliminate food waste starts with investing in our people. We provide a comprehensive support system designed to help you do your best work while maintaining a healthy, balanced life.
Comprehensive Health & Wellness: Comprehensive medical, dental, and vision coverage for you and your family, with the majority of premiums covered by Afresh. We also provide dedicated mental health support and counseling services.
Invested in Your Future: Competitive base salary, meaningful equity (U.S. employees), and a 401(k) program with a generous company match.
Flexible & Modern Workspace: Whether you work from home or a local office, we support your setup with a home office stipend and "Coworking Wallets" for flexible workspace access.
Growth-Obsessed Culture: We believe in continuous learning. Every employee receives an annual professional development budget to master new skills and grow their career at Afresh.
Holistic Monthly Stipends: Beyond your paycheck, we provide monthly stipends for "Betterment" (wellness/lifestyle) and telecommunications to ensure you have what you need to thrive.
Time to Recharge: Flexible paid time off to take the time you need to recharge.
*Full-time U.S. employees are eligible for these benefits
About Afresh
Founded in 2017, Afresh is using AI to tackle the #1 solution to curb climate change: reducing food waste. By building AI specifically for the intricacies of grocery—from the fresh perimeter to the center store—we help grocers minimize waste and maximize sales.
Afresh sits at an incredible intersection of positive social impact, rocket ship financial growth, and cutting-edge technology. Our best-in-class AI research has been published in top journals, including ICML, and our investors include Al Gore’s Just Climate, former Whole Foods Market CEO Walter Robb, and Eric Schmidt's Innovation Endeavors.
Grocery is the past, present, and future of our food system – the waste we create today will impact our planet for years to come. Join us as we continue to build a vibrant, diverse, and inclusive team that embodies our company’s values of proactivity, kindness, candor, and humility.
Afresh provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity/expression, marital status, pregnancy or related condition, or any other basis protected by law.
Here at Afresh, many of our employees work remotely provided that they reside in one of the following states: AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WI.
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This role is hybrid and based in San Francisco, CA, with 3 days per week onsite in our headquarters. Are you currently based in or able to relocate to the San Francisco Bay Area, and able to work on-site in a hybrid capacity?*
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Briefly describe a project where you had to embed with a customer's technical team, understand their existing data/systems, and build something to move them forward.*
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Listed by Afresh for a position based in the United States. Employers on this board attest they are hiring domestically.
Staff AI Platform Engineer
Afresh · San Francisco, CA
Pay
$169k–273k
Setting
On-site
Back to jobs
Staff AI Platform Engineer
San Francisco, CA
Apply
Afresh, the AI platform for grocery, began by tackling the most complex problem in the industry: fresh, and has evolved into the core AI platform for grocers.
By leveraging proprietary AI designed for high-volatility environments, we empower partners like Albertsons, Meijer, and Wakefern to drive smarter decisions across their entire enterprise.
Following record-breaking 70% revenue growth in 2025, we have scaled to 6 enterprise-grade solutions, with solutions live in over 10% of the U.S. grocery market. Our platform now orchestrates billions of decisions from the store floor to the distribution center and prevented over 200 million pounds of food waste last year alone.
If you're looking for a role where your work directly translates into massive scale and social good, and you want to be part of the team that defines how the world eats, there is no better time to join us.
About the Role
Frontier models are a commodity. The knowledge you feed them is not.
As a Staff AI Platform Engineer, you build the AI and data platform that powers Afresh's products: the knowledge and retrieval layer that makes grocery data reliably usable by LLMs, the agent systems built on top of it, and the evaluation and serving infrastructure underneath. Your "customers" are Afresh's own engineers and AI products — your job is to give them a platform that turns raw grocery data into context a model can be trusted with, at production quality.
This is senior, 0-to-1 platform work. You'll make foundational choices about how we represent grocery knowledge, ground our models, and measure whether any of it is actually working — in a fast-moving space with no playbook.
What You’ll Do
Build the knowledge & retrieval layer
Design and operate the knowledge graph and ontology that capture how grocery data relates.
Build the retrieval systems (vector, graph, and structured) that feed the right context to our models — so grounding is reliable, not lucky.
Build and serve the agent platform
Build LLM-powered agents (tool-use, multi-step reasoning, orchestration) and the serving infrastructure to run them reliably and cost-effectively.
Build the tools, abstractions, and interfaces other engineers depend on — a platform, not one-off features.
Own evaluation, quality, and the data foundation
Stand up eval sets, LLM-as-judge harnesses, tracing, and observability, plus the metrics (faithfulness, accuracy, hallucination rate, latency, cost) that tell us whether a change helped or hurt.
Build the pipelines, data products, and experimentation on Databricks/MLflow that take work from prototype to production — and partner with the engineers deploying our AI in the field to harden what works into reusable capabilities.
What Makes You a Good Fit
We encourage all highly-qualified candidates to apply, even if they do not fulfill all the listed criteria.
5+ years building production software, data, or ML systems; an excellent engineer with strong systems and API design (Python).
Hands-on production experience with LLM systems: retrieval/RAG, agents and tool-use, prompt and context engineering — and, critically, evaluation. You measure quality; you don't eyeball it.
Solid data-engineering and data-platform foundations: pipelines, data modeling, and a modern cloud data stack (Databricks/Spark, MLflow, cloud warehouses).
Comfort in the messy middle of AI systems — retrieval quality, latency and cost trade-offs, non-determinism — and the instinct to build the guardrails and evals that make them trustworthy.
A platform mindset: you build for leverage and clean interfaces, and you thrive in ambiguity in a fast-moving space.
Nice to Have
Knowledge graphs, ontologies, or semantic layers in production; graph databases.
Vector stores (pgvector, Pinecone, Weaviate, etc.) and hybrid search.
MCP or similar tool/context protocols; agent frameworks (e.g., LangGraph).
MLOps and model serving at scale; experimentation and observability tooling for LLM systems.
Experience in grocery, retail, or other complex enterprise data domains.
Our Tech Stack
Python, PySpark, dbt
Databricks (Delta Lake, Unity Catalog, MLflow)
Astronomer (Airflow) for orchestration
LLMs and agents (Claude), retrieval over vector + graph stores, MCP tooling, eval and observability harnesses
Claude, GitHub, Shortcut, Notion for development workflows
Why Afresh?
We're a mission-driven company that eliminates hundreds of millions of pounds of food waste in grocery stores every year — your platform powers products with direct, visible impact.
Build the foundation the rest of the product stands on: high-leverage, 0-to-1 work where your abstractions make the whole team faster.
Be part of an engineering culture that's genuinely AI-forward — we want to be on the bleeding edge of agentic systems, not watching from the sidelines.
Senior team, high trust, and real ownership at a pivotal inflection point for how Afresh scales.
Collaborative, supportive environment & awesome people :)
This is a hybrid role based in the San Francisco office (3 days/week)
This position is not eligible for company sponsorship.
Salary Band in U.S. (USD): $168,912-$253,368 + meaningful early-stage equity + benefits
Why You’ll Love Working at Afresh
At Afresh, our mission to eliminate food waste starts with investing in our people. We provide a comprehensive support system designed to help you do your best work while maintaining a healthy, balanced life.
Comprehensive Health & Wellness: Comprehensive medical, dental, and vision coverage for you and your family, with the majority of premiums covered by Afresh. We also provide dedicated mental health support and counseling services.
Invested in Your Future: Competitive base salary, meaningful equity (U.S. employees), and a 401(k) program with a generous company match.
Flexible & Modern Workspace: Whether you work from home or a local office, we support your setup with a home office stipend and "Coworking Wallets" for flexible workspace access.
Growth-Obsessed Culture: We believe in continuous learning. Every employee receives an annual professional development budget to master new skills and grow their career at Afresh.
Holistic Monthly Stipends: Beyond your paycheck, we provide monthly stipends for "Betterment" (wellness/lifestyle) and telecommunications to ensure you have what you need to thrive.
Time to Recharge: Flexible paid time off to take the time you need to recharge.
*Full-time U.S. employees are eligible for these benefits
About Afresh
Founded in 2017, Afresh is using AI to tackle the #1 solution to curb climate change: reducing food waste. By building AI specifically for the intricacies of grocery—from the fresh perimeter to the center store—we help grocers minimize waste and maximize sales.
Afresh sits at an incredible intersection of positive social impact, rocket ship financial growth, and cutting-edge technology. Our best-in-class AI research has been published in top journals, including ICML, and our investors include Al Gore’s Just Climate, former Whole Foods Market CEO Walter Robb, and Eric Schmidt's Innovation Endeavors.
Grocery is the past, present, and future of our food system – the waste we create today will impact our planet for years to come. Join us as we continue to build a vibrant, diverse, and inclusive team that embodies our company’s values of proactivity, kindness, candor, and humility.
Afresh provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity/expression, marital status, pregnancy or related condition, or any other basis protected by law.
Here at Afresh, many of our employees work remotely provided that they reside in one of the following states: AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WI.
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Do you have unrestricted work authorization in the United States? *
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Will you now, or in the future, require immigration sponsorship for continued employment in the United States?*
Select...
This role is hybrid and based in San Francisco, CA, with 3 days per week onsite in our headquarters. Are you currently based in or able to relocate to the San Francisco Bay Area, and able to work on-site in a hybrid capacity?*
Select...
Do you have 3+ years of professional experience building production software, data, or ML systems, with strong systems and API design skills in Python?*
Select...
Have you personally designed, built, and shipped a production AI/ML or LLM-based system at your current or a previous company (not a prototype, hackathon project, or demo)?*
Select...
Briefly describe the production AI system you built: what it does, your role, and what "production" meant in that context (e.g., scale, uptime, real users/data). *
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Listed by Afresh for a position based in the United States. Employers on this board attest they are hiring domestically.
Senior AI Platform Engineer
Afresh · San Francisco, CA
Pay
$156k–231k
Setting
On-site
Back to jobs
Senior AI Platform Engineer
San Francisco, CA
Apply
Afresh, the AI platform for grocery, began by tackling the most complex problem in the industry: fresh, and has evolved into the core AI platform for grocers.
By leveraging proprietary AI designed for high-volatility environments, we empower partners like Albertsons, Meijer, and Wakefern to drive smarter decisions across their entire enterprise.
Following record-breaking 70% revenue growth in 2025, we have scaled to 6 enterprise-grade solutions, with solutions live in over 10% of the U.S. grocery market. Our platform now orchestrates billions of decisions from the store floor to the distribution center and prevented over 200 million pounds of food waste last year alone.
If you're looking for a role where your work directly translates into massive scale and social good, and you want to be part of the team that defines how the world eats, there is no better time to join us.
About the Role
Frontier models are a commodity. The knowledge you feed them is not.
As a Senior AI Platform Engineer, you build the AI and data platform that powers Afresh's products: the knowledge and retrieval layer that makes grocery data reliably usable by LLMs, the agent systems built on top of it, and the evaluation and serving infrastructure underneath. Your "customers" are Afresh's own engineers and AI products — your job is to give them a platform that turns raw grocery data into context a model can be trusted with, at production quality.
This is senior, 0-to-1 platform work. You'll make foundational choices about how we represent grocery knowledge, ground our models, and measure whether any of it is actually working — in a fast-moving space with no playbook.
What You’ll Do
Build the knowledge & retrieval layer
Design and operate the knowledge graph and ontology that capture how grocery data relates.
Build the retrieval systems (vector, graph, and structured) that feed the right context to our models — so grounding is reliable, not lucky.
Build and serve the agent platform
Build LLM-powered agents (tool-use, multi-step reasoning, orchestration) and the serving infrastructure to run them reliably and cost-effectively.
Build the tools, abstractions, and interfaces other engineers depend on — a platform, not one-off features.
Own evaluation, quality, and the data foundation
Stand up eval sets, LLM-as-judge harnesses, tracing, and observability, plus the metrics (faithfulness, accuracy, hallucination rate, latency, cost) that tell us whether a change helped or hurt.
Build the pipelines, data products, and experimentation on Databricks/MLflow that take work from prototype to production — and partner with the engineers deploying our AI in the field to harden what works into reusable capabilities.
What Makes You a Good Fit
We encourage all highly-qualified candidates to apply, even if they do not fulfill all the listed criteria.
3+ years building production software, data, or ML systems; an excellent engineer with strong systems and API design (Python).
Hands-on production experience with LLM systems: retrieval/RAG, agents and tool-use, prompt and context engineering — and, critically, evaluation. You measure quality; you don't eyeball it.
Solid data-engineering and data-platform foundations: pipelines, data modeling, and a modern cloud data stack (Databricks/Spark, MLflow, cloud warehouses).
Comfort in the messy middle of AI systems — retrieval quality, latency and cost trade-offs, non-determinism — and the instinct to build the guardrails and evals that make them trustworthy.
A platform mindset: you build for leverage and clean interfaces, and you thrive in ambiguity in a fast-moving space.
Nice to Have
Knowledge graphs, ontologies, or semantic layers in production; graph databases.
Vector stores (pgvector, Pinecone, Weaviate, etc.) and hybrid search.
MCP or similar tool/context protocols; agent frameworks (e.g., LangGraph).
MLOps and model serving at scale; experimentation and observability tooling for LLM systems.
Experience in grocery, retail, or other complex enterprise data domains.
Our Tech Stack
Python, PySpark, dbt
Databricks (Delta Lake, Unity Catalog, MLflow)
Astronomer (Airflow) for orchestration
LLMs and agents (Claude), retrieval over vector + graph stores, MCP tooling, eval and observability harnesses
Claude, GitHub, Shortcut, Notion for development workflows
Why Afresh
We're a mission-driven company that eliminates hundreds of millions of pounds of food waste in grocery stores every year — your platform powers products with direct, visible impact.
Build the foundation the rest of the product stands on: high-leverage, 0-to-1 work where your abstractions make the whole team faster.
Be part of an engineering culture that's genuinely AI-forward — we want to be on the bleeding edge of agentic systems, not watching from the sidelines.
Senior team, high trust, and real ownership at a pivotal inflection point for how Afresh scales.
Collaborative, supportive environment & awesome people :)
This is a hybrid role based in the San Francisco office (3 days/week)
This position is not eligible for company sponsorship.
Salary Range in U.S.: $156,060 - $211,140 + meaningful early-stage equity + benefits
Why You’ll Love Working at Afresh
At Afresh, our mission to eliminate food waste starts with investing in our people. We provide a comprehensive support system designed to help you do your best work while maintaining a healthy, balanced life.
Comprehensive Health & Wellness: Comprehensive medical, dental, and vision coverage for you and your family, with the majority of premiums covered by Afresh. We also provide dedicated mental health support and counseling services.
Invested in Your Future: Competitive base salary, meaningful equity (U.S. employees), and a 401(k) program with a generous company match.
Flexible & Modern Workspace: Whether you work from home or a local office, we support your setup with a home office stipend and "Coworking Wallets" for flexible workspace access.
Growth-Obsessed Culture: We believe in continuous learning. Every employee receives an annual professional development budget to master new skills and grow their career at Afresh.
Holistic Monthly Stipends: Beyond your paycheck, we provide monthly stipends for "Betterment" (wellness/lifestyle) and telecommunications to ensure you have what you need to thrive.
Time to Recharge: Flexible paid time off to take the time you need to recharge.
*Full-time U.S. employees are eligible for these benefits
About Afresh
Founded in 2017, Afresh is using AI to tackle the #1 solution to curb climate change: reducing food waste. By building AI specifically for the intricacies of grocery—from the fresh perimeter to the center store—we help grocers minimize waste and maximize sales.
Afresh sits at an incredible intersection of positive social impact, rocket ship financial growth, and cutting-edge technology. Our best-in-class AI research has been published in top journals, including ICML, and our investors include Al Gore’s Just Climate, former Whole Foods Market CEO Walter Robb, and Eric Schmidt's Innovation Endeavors.
Grocery is the past, present, and future of our food system – the waste we create today will impact our planet for years to come. Join us as we continue to build a vibrant, diverse, and inclusive team that embodies our company’s values of proactivity, kindness, candor, and humility.
Afresh provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity/expression, marital status, pregnancy or related condition, or any other basis protected by law.
Here at Afresh, many of our employees work remotely provided that they reside in one of the following states: AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WI.
Create a Job Alert
Interested in building your career at Afresh? Get future opportunities sent straight to your email.
Create alert
Apply for this job
*
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Autofill my application
First Name*
Last Name*
Preferred First Name
Email*
Phone
Country
Phone
Resume/CV
Attach
Attach
Dropbox
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Enter manually
Accepted file types: pdf, doc, docx, txt, rtf
Cover Letter
Attach
Attach
Dropbox
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Enter manually
Accepted file types: pdf, doc, docx, txt, rtf
Do you have unrestricted work authorization in the United States? *
Select...
Will you now, or in the future, require immigration sponsorship for continued employment in the United States?*
Select...
This role is hybrid and based in San Francisco, CA, with 3 days per week onsite in our headquarters. Are you currently based in or able to relocate to the San Francisco Bay Area, and able to work on-site in a hybrid capacity?*
Select...
Do you have 3+ years of professional experience building production software, data, or ML systems, with strong systems and API design skills in Python?*
Select...
Have you personally designed, built, and shipped a production AI/ML or LLM-based system at your current or a previous company (not a prototype, hackathon project, or demo)?*
Select...
Briefly describe the production AI system you built: what it does, your role, and what "production" meant in that context (e.g., scale, uptime, real users/data). *
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Listed by Afresh for a position based in the United States. Employers on this board attest they are hiring domestically.
Senior Forward Deployed Engineer
Afresh · San Francisco, CA
Pay
$156k–231k
Setting
On-site
Back to jobs
Senior Forward Deployed Engineer
San Francisco, CA
Apply
Afresh, the AI platform for grocery, began by tackling the most complex problem in the industry: fresh, and has evolved into the core AI platform for grocers.
By leveraging proprietary AI designed for high-volatility environments, we empower partners like Albertsons, Meijer, and Wakefern to drive smarter decisions across their entire enterprise.
Following record-breaking 70% revenue growth in 2025, we have scaled to 6 enterprise-grade solutions, with solutions live in over 10% of the U.S. grocery market. Our platform now orchestrates billions of decisions from the store floor to the distribution center and prevented over 200 million pounds of food waste last year alone.
If you're looking for a role where your work directly translates into massive scale and social good, and you want to be part of the team that defines how the world eats, there is no better time to join us.
About the Role
Most companies make you choose: build the platform, or go deploy it. Here you do both — and that's the point.
As a Forward Deployed AI Engineer, you're part of a single team that both delivers Afresh's AI into enterprise grocery customers and builds the platform that makes that delivery fast. You'll spend dedicated time in the field — embedded with a customer, integrating into their data, shipping AI systems on top of it — and dedicated time on the platform, turning what you just learned into reusable tooling the whole team deploys next. You build the house you live in.
Afresh leads the customer relationship and direction; you and a small team bring the technical firepower — scope and architect the work with the customer, then build it. Because you also own the platform underneath, the rough edges you hit in the field become the things you fix at the root.
This is senior, hands-on, 0-to-1 work in a space with no playbook.
What You'll Do
In the field (forward deployed)
Partner with Afresh's account lead and the customer's technical teams to scope and architect the work — the data sources, the architecture, and the path to production.
Embed with the customer's data and engineering teams (remote and on-site); integrate into their cloud and data platform; build production-grade pipelines and model messy enterprise data into trustworthy data products.
Design and ship LLM- and agent-powered systems on that data — retrieval, agentic workflows, data-quality and analytics agents — reliable enough to run in production, not just to demo.
On the platform (building the house you live in)
Harden what works in the field into the shared platform: the knowledge and grounding layer (knowledge graph, ontology, and retrieval) that makes grocery data usable by LLMs, the agent frameworks, and the serving infrastructure.
Build the evals, tracing, and tooling that let the team measure quality — accuracy, hallucination rate, latency, cost — and ship faster on the next customer.
Build for leverage: clean interfaces and reusable building blocks, not one-off per-customer code.
Across both
Own the flywheel: field learnings flow straight into the platform, and platform improvements show up at the next customer.
What Makes You a Great Fit
We encourage all highly-qualified candidates to apply, even if they do not fulfill all the listed criteria.
3+ years building production software and data systems, with strong, production-grade code
An architect's instinct: you can take an ambiguous problem and a messy data landscape, design a clean and workable solution, and then build it.
Genuine AI/LLM depth — you've built real systems with LLMs and agents (retrieval/RAG, tool-use) and you evaluate quality rather than eyeball it.
Real data-engineering depth: building and operating data pipelines, modeling messy enterprise data, and working in a modern cloud data platform (Databricks, BigQuery, Snowflake, or similar).
Range across both modes — you genuinely like being in front of customers and going heads-down to build reusable infrastructure, and you can switch between them without one suffering. This is the role's defining trait.
Customer-facing comfort: you work well with a customer's engineers and data teams — running working sessions, explaining your thinking, and earning trust through what you deliver.
A bias toward ownership and momentum, and comfort traveling to customer sites regularly (~10-20%).
Nice to Have
Experience in grocery, retail, or supply chain data domains.
Knowledge graphs, ontologies, or semantic layers in production; graph and vector stores (pgvector, Pinecone, Weaviate) and hybrid search.
MCP or similar tool/context protocols; agent frameworks (e.g., LangGraph); MLOps, model serving, and observability for LLM systems.
Prior forward-deployed, solutions, or implementation engineering — or early-stage startup experience navigating rapid customer expansion.
Why Afresh?
We're a mission-driven company that eliminates hundreds of millions of pounds of food waste in grocery stores every year — your work has direct, visible impact.
You'll do both halves of the job: deploy with customers and build the platform you deploy — never a body-shop consultant, never an ivory-tower platform engineer.
Be part of an engineering culture that's genuinely AI-forward — we want to be on the bleeding edge of agentic development, not watching from the sidelines.
Senior team, high trust, and real ownership at a pivotal inflection point for how Afresh scales.
Collaborative, supportive environment & awesome people
This is a hybrid role based in the San Francisco office (3 days/week)
This position is not eligible for company sponsorship.
Salary Range in U.S.: $156,060 - $211,140 + meaningful early-stage equity + benefits
Why You’ll Love Working at Afresh
At Afresh, our mission to eliminate food waste starts with investing in our people. We provide a comprehensive support system designed to help you do your best work while maintaining a healthy, balanced life.
Comprehensive Health & Wellness: Comprehensive medical, dental, and vision coverage for you and your family, with the majority of premiums covered by Afresh. We also provide dedicated mental health support and counseling services.
Invested in Your Future: Competitive base salary, meaningful equity (U.S. employees), and a 401(k) program with a generous company match.
Flexible & Modern Workspace: Whether you work from home or a local office, we support your setup with a home office stipend and "Coworking Wallets" for flexible workspace access.
Growth-Obsessed Culture: We believe in continuous learning. Every employee receives an annual professional development budget to master new skills and grow their career at Afresh.
Holistic Monthly Stipends: Beyond your paycheck, we provide monthly stipends for "Betterment" (wellness/lifestyle) and telecommunications to ensure you have what you need to thrive.
Time to Recharge: Flexible paid time off to take the time you need to recharge.
*Full-time U.S. employees are eligible for these benefits
About Afresh
Founded in 2017, Afresh is using AI to tackle the #1 solution to curb climate change: reducing food waste. By building AI specifically for the intricacies of grocery—from the fresh perimeter to the center store—we help grocers minimize waste and maximize sales.
Afresh sits at an incredible intersection of positive social impact, rocket ship financial growth, and cutting-edge technology. Our best-in-class AI research has been published in top journals, including ICML, and our investors include Al Gore’s Just Climate, former Whole Foods Market CEO Walter Robb, and Eric Schmidt's Innovation Endeavors.
Grocery is the past, present, and future of our food system – the waste we create today will impact our planet for years to come. Join us as we continue to build a vibrant, diverse, and inclusive team that embodies our company’s values of proactivity, kindness, candor, and humility.
Afresh provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity/expression, marital status, pregnancy or related condition, or any other basis protected by law.
Here at Afresh, many of our employees work remotely provided that they reside in one of the following states: AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WI.
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Staff Software Engineer Data - DC Tech Lead
Afresh · Remote - United States
Pay
$168k–273k
Setting
Remote
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Staff Software Engineer Data / Tech Lead (Distribution Center)
Remote - United States
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Afresh, the AI platform for grocery, began by tackling the most complex problem in the industry: fresh, and has evolved into the core AI platform for grocers.
By leveraging proprietary AI designed for high-volatility environments, we empower partners like Albertsons, Meijer, and Wakefern to drive smarter decisions across their entire enterprise.
Following record-breaking 70% revenue growth in 2025, we have scaled to 6 enterprise-grade solutions, with solutions live in over 10% of the U.S. grocery market. Our platform now orchestrates billions of decisions from the store floor to the distribution center and prevented over 200 million pounds of food waste last year alone.
If you're looking for a role where your work directly translates into massive scale and social good, and you want to be part of the team that defines how the world eats, there is no better time to join us.
About the Role
As a Staff Data Engineer, on the Distribution Center (DC) Solutions team, you’ll play a technical lead role in building and scaling the data integrations needed to support our suite of DC products. You will design and implement ETLs that reliably process large volumes of customer-provided data and build tools/improve the platform to make customer integrations faster, more accurate, and more scalable. Your work will have a direct and visible impact on our ability to onboard customers more easily and quickly and power our machine learning grocery solution.
What You’ll Do
Engineering & Data Pipelines: Design, build, and optimize robust ETLs using PySpark and DBT to process large-scale customer datasets while developing tools and frameworks to streamline data integrations and improve scalability.
Technical Leadership & Strategy: Define the technical vision for DC data architecture, mentor engineers, and manage external contractors to ensure the team delivers high-quality, practical solutions for current and future needs.
Cross-functional Collaboration: Partner with product, engineering, and applied science teams to scope work and deliver data solutions that address real-world challenges in customer data quality and product feature requirements.
What Makes You a Great Fit
We encourage all highly-qualified candidates to apply, even if they don’t meet every listed qualification.
Significant experience designing and maintaining ETLs that process large-scale datasets.
Proficiency with Python, PySpark, SQL, and experience working on platforms/tools like Databricks, Snowflake, or DBT.
2+ years experience in a technical lead role (e.g. Tech Lead or Engineering Manager), with a willingness to mentor and help others grow.
Strong problem-solving skills and the ability to work with ambiguous or incomplete requirements to deliver concrete, impactful solutions.
A focus on practical outcomes—you're skilled at balancing technical rigor with the need to get things done.
Experience working directly with complex, unclean datasets and finding innovative ways to process and analyze them.
A knack for identifying areas where tooling or automation can simplify workflows and reduce manual effort.
Excellent communication skills—you’re able to explain your ideas clearly to both technical and non-technical audiences.
We’re looking for someone who thrives on tackling complex data problems and takes pride in building systems that work seamlessly at scale. If that sounds like you, we’d love to hear from you!
This position is not eligible for immigration sponsorship
Salary Range in US: $168K - $253K + meaningful early-stage equity + benefits
Why You’ll Love Working at Afresh
At Afresh, our mission to eliminate food waste starts with investing in our people. We provide a comprehensive support system designed to help you do your best work while maintaining a healthy, balanced life.
Comprehensive Health & Wellness: Comprehensive medical, dental, and vision coverage for you and your family, with the majority of premiums covered by Afresh. We also provide dedicated mental health support and counseling services.
Invested in Your Future: Competitive base salary, meaningful equity (U.S. employees), and a 401(k) program with a generous company match.
Flexible & Modern Workspace: Whether you work from home or a local office, we support your setup with a home office stipend and "Coworking Wallets" for flexible workspace access.
Growth-Obsessed Culture: We believe in continuous learning. Every employee receives an annual professional development budget to master new skills and grow their career at Afresh.
Holistic Monthly Stipends: Beyond your paycheck, we provide monthly stipends for "Betterment" (wellness/lifestyle) and telecommunications to ensure you have what you need to thrive.
Time to Recharge: Flexible paid time off to take the time you need to recharge.
*Full-time U.S. employees are eligible for these benefits
About Afresh
Founded in 2017, Afresh is using AI to tackle the #1 solution to curb climate change: reducing food waste. By building AI specifically for the intricacies of grocery—from the fresh perimeter to the center store—we help grocers minimize waste and maximize sales.
Afresh sits at an incredible intersection of positive social impact, rocket ship financial growth, and cutting-edge technology. Our best-in-class AI research has been published in top journals, including ICML, and our investors include Al Gore’s Just Climate, former Whole Foods Market CEO Walter Robb, and Eric Schmidt's Innovation Endeavors.
Grocery is the past, present, and future of our food system – the waste we create today will impact our planet for years to come. Join us as we continue to build a vibrant, diverse, and inclusive team that embodies our company’s values of proactivity, kindness, candor, and humility.
Afresh provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity/expression, marital status, pregnancy or related condition, or any other basis protected by law.
Here at Afresh, many of our employees work remotely provided that they reside in one of the following states: AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WI.
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