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ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes - Travel to customers up to 40% of the time WHAT YOU’LL BRING - 6+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $150,000–$250,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Listed by LangChain for a position based in the United States. Employers on this board attest they are hiring domestically.

Engineering

44 days ago

Deployed Engineer (Early Career- SF)

LangChain · United States

Pay

$160k–175k

Setting

Remote

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ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM This team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE You'll work on some of the hardest problems in applied AI alongside customers. You will help customers adopt innovative new practices in agentic engineering, and ensure they ship reliable agents into production, quickly. The feedback loop is fast, the impact is visible, and your work directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams and customers - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Build and run tailored demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Interface with LangChain's engineering, product and design (EPD) team to share field perspectives and guide product direction based on customer priorities - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement WHAT YOU’LL BRING - 1-3 years of experience in software engineering, customer engineering, solutions engineering, founding engineering, or a similarly technical role, ideally at a startup or high-growth company - Strong Python, JavaScript and systems fundamentals - Hands-on experience building and deploying agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Strong technical communication skills and builder credibility; Can explain technical tradeoffs clearly, translate complex AI concepts into actionable insights, and build trust with technical customers and engineering teams - Excited to work directly with customers during POCs, architecture reviews, and technical evaluations - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about shipping AI agents in production NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $160,000-175,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Listed by LangChain for a position based in the United States. Employers on this board attest they are hiring domestically.

Engineering

61 days ago

IT Systems Engineer

LangChain · United States

Pay

$150k

Setting

Remote

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ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE ROLE We are seeking our second IT Engineer to join our growing team in San Francisco. Our team laid the foundation for IT at LangChain, and this role is critical to helping us mature and scale that foundation as the company grows. You'll bring deep technical expertise to our fleet management and SaaS administration, with room to shape how we manage our fleet, identity, SaaS stack, and the automation that runs the business. The ideal candidate brings startup experience, thrives in ambiguity, loves a good problem, and is excited to build scalable systems that support our global team. WHAT YOU'LL DO Infrastructure & Automation - Build and maintain our IT infrastructure and tech stack that scales with LangChain’s rapid growth - Drive automation initiatives to reduce toil and improve efficiency using scripts, APIs, and workflow tools - Implement monitoring and documentation practices that enable operational excellence Client Platform Engineering - Reimagine how we deploy, configure, and manage our Mac fleet. MDM (Iru) is the foundation, not the entire solution however. - Design and build a secure, reliable, and maintainable desktop environment that replaces our current patchwork of one-off scripts with version-controlled, testable, and repeatable systems - Own our approach to custom security controls and application deployment across the fleet, so updates and configuration changes are consistent and easy to roll out at scale - Build the fleet management systems now so they hold up as headcount, and the fleet, keep growing Security & Identity Management - Drive our identity strategy, implementing secure, scalable access controls following the principle of least privilege - Identify and implement security enhancements across our SaaS stack - Partner with our Security team to drive improvement of our enterprise security posture SaaS Administration - Administer and optimize our growing SaaS stack, managing provisioning, access controls, and lifecycle management - Become IT's central administrator for LangSmith, our own product, developing deep fluency in its administration surface - Build automated workflows for LangSmith administration using its API paired with our automation tooling, reducing manual, toil-heavy admin work - Help IT stay fluent across the internal tools we run and support, including the LLM Gateway. Another LangChain product. Core IT Operations - Provide support to employees globally across hardware, software, networking, and IT tools - Deliver great onboarding experiences for new hires, ensuring they have the right hardware, access, and setup so they can be productive from day one WHAT YOU'LL BRING - 5+ years of experience in IT engineering and systems administration - Deep proficiency with Okta and Okta Workflows - Fluency in at least one general-purpose programming language (Python, JavaScript, or similar) with demonstrated ability to write production-quality scripts and automation - Versed in the us of REST APIs, webhooks, and API authentication methods; you should be comfortable reading API documentation and building integrations between systems - Demonstrated ability to build meaningful automations that reduce manual work and improve IT operations - Hands-on experience with IaC using Terraform to manage and provision IT infrastructure and applications, and comfort applying changes within an existing Terraform codebase - Experience using coding agents (e.g. Claude Code) as part of your day-to-day engineering workflow to build and ship automation faster - Strong experience with a modern tech stack that includes Google Workspace, Slack, Notion, Claude, ChatGPT - Solid understanding of MDM platforms, and ideally experience going beyond baseline MDM with fleet/configuration management tooling to manage a fleet's security and application needs - Experience administering a large or complex SaaS stack, ideally including internal or AI/LLM-based products - Strong networking fundamentals (TCP/IP, DNS, VPNs, firewalls, switching, wireless, LAN/WAN) - Annual salary range: $150,000-$170,00 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Listed by LangChain for a position based in the United States. Employers on this board attest they are hiring domestically.

Engineering

71 days ago

Software Engineering Manager, Database (SmithDB)

LangChain · United States

Pay

$240k–300k

Setting

Remote

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ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. About the team SmithDB is LangChain's internal database team. We're building a storage and query layer purpose-built for AI observability and evaluation. Within six months we went from idea to a production system that offers industry leading performance and scalability for agent observability data. We're a small, fast team of systems engineers tackling genuinely hard problems: storage layout, query execution, compaction, and scaling toward trillions of agent traces. We develop in Rust, run on Kubernetes, and integrate tightly with S3/GCS/Azure Blob. There are no legacy constraints; this is a greenfield system with real production load and ambitious engineering goals. About the role We're looking for a hands-on Engineering Manager to lead the SmithDB team. This is not a pure people-management role. You'll write production code, review PRs at the systems level, make architectural calls, and be in the weeds alongside your engineers. At the same time, you'll own team health, hiring, technical roadmap, and coordination with the broader LangSmith platform. The ideal candidate has deep systems or database engineering experience and genuinely prefers to stay technical while growing a team. What you'll do - Write and review production Rust code across ingestion, query execution, and storage layers - Lead architectural decisions on storage format, compaction, indexing, and query planning - Drive performance investigations using memory and CPU profiling tools; own the path from profiling to shipped fix - Design and harden the distributed deployment of SmithDB services on Kubernetes (multi-tenant, high-throughput, low-latency) - Contribute to cloud object store integrations (S3, GCS, Azure Blob) and set the standard for how SmithDB manages data at rest and in flight - Build and maintain observability for the engine itself: metrics, tracing, debug tooling - Manage a small but growing team of systems engineers: set goals, run 1:1s, provide technical mentorship, and grow careers - Own the SmithDB technical roadmap in partnership with LangSmith product and engineering leadership - Communicate progress, risks, and tradeoffs clearly to the broader organization: you write concise, decision-ready updates What you'll bring - 7+ years in systems or database engineering, with at least 2 years in a technical lead or engineering management role - Production Rust experience — you can write it, review it, and have opinions on how to structure it at scale - Deep understanding of database or storage engine internals: query execution, storage layouts, indexing, compaction - Proficiency in systems performance analysis: memory allocators, CPU hotspots, lock contention, async runtimes (Tokio) - Experience deploying and operating distributed services on Kubernetes in a production, multi-tenant environment - Familiarity with cloud object storage (S3-compatible APIs, consistency models, cost/performance tradeoffs) - Proven track record of managing engineers — you can recruit, retain, and level-up a team without losing your technical edge Nice-to-have: - Experience building or contributing to columnar storage formats (Parquet, Arrow), OLAP query engines, or time-series stores - Background in observability infrastructure or tracing pipelines (OpenTelemetry, ClickHouse, Prometheus) - Experience scaling a system from early-stage to hundreds of billions / trillions of records Compensation Salary Range: $240,000-$300,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Listed by LangChain for a position based in the United States. Employers on this board attest they are hiring domestically.

Engineering

118 days ago

Sales Engineer (Bay Area)

LangChain · United States

Pay

$185k–315k

Setting

Remote

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ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM This team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Sales Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE You'll work on some of the hardest problems in applied AI alongside customers. This is not demos or research, but helping teams build systems they rely on in production. The feedback loop is fast, the impact is visible, and your work directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $185,000–$315,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Listed by LangChain for a position based in the United States. Employers on this board attest they are hiring domestically.

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