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This website uses cookies We use cookies to personalise content and ads, to provide social media features and to analyse our traffic. We also share information about your use of our site with our social media, advertising and analytics partners who may combine it with other information that you’ve provided to them or that they’ve collected from your use of their services. Show details Allow all Deny Skip to content home about labs careers contact human agent join the waitlist join the waitlist ← Careers Member of Technical Staff, Infrastructure Infrastructure · Palo Alto · Full-Time Build and operate the secure execution substrate for enterprise agents, customer applications, and Sycamore’s control plane. About Sycamore Sycamore is building the trusted agent operating system for the enterprise. Our platform helps companies build, deploy, and orchestrate AI agents that take on real operational work, with the security and control large organizations need. We are a small, engineering-led team working directly with Fortune 500 enterprises. We have raised $65M from Coatue and Lightspeed, along with other investors and industry leaders. Where you could focus This is software engineering for consequential distributed systems, not cloud administration: control-plane services and Kubernetes controllers, identity and network boundaries, tenant-isolated data, and failures that cross application, cluster, database, and customer-network layers. Infrastructure is the foundation beneath Product and Core AI, so an error here can affect every application and customer. The team covers three areas. They share an on-call rotation and a great many failures, so nobody works in only one, and you should not try to pick before talking to us. The platform and control plane. Kubernetes-based serving, the sandboxes agents execute in, deployment and rollback, networking and identity, and the operators that reconcile all of it. This is where blast radius is decided. The data platform. This is database platform engineering, and it is worth being precise, because the phrase invites a different assumption: there is no warehouse, no dbt, and no analytics pipeline waiting for an owner. What we have is a large and growing fleet of PostgreSQL databases carrying enterprise customer data under a genuine isolation requirement, hundreds of migrations across many trees and authors, a connection budget that is a real ceiling, retention obligations measured in years, and a hybrid full-text and vector retrieval path sitting in the hot path of every agent conversation. The problems are fleet-shaped: a migration is easy, and applying it safely across every tenant database with per-tenant failure isolation and no downtime is not. Reliability. How the platform behaves over time: service level objectives and error budgets that mean something, an observability estate managed as code, promotion gates that decide whether a release reaches production, capacity and cold-start performance, and incident response from page through postmortem to the structural fix. We are honest about where this stands. We have a large monitor fleet and an enforced metric taxonomy, but few service level objectives, no error budgets, no burn-rate alerting, and a promotion gate that warns rather than blocks. Building that practice is the work, not a side project within it. What you will do Build and operate Kubernetes-based serving and sandbox platforms for agents, internal services, and customer applications. Develop infrastructure-as-code, Helm charts, provisioning services, admission controls, and operators that reconcile environments safely. Maintain production change controls, drift detection, release gates, and fail-safe rollout procedures. Own the database fleet: schema topology and migration safety, provisioning and credential rotation, pooling and connection economics, isolation guarantees, retention and partitioning, and the search and embedding path. Define service level indicators and objectives, establish error budgets, and build the burn-rate alerting that makes them actionable. Own the observability estate as code: monitors, dashboards, tracing, metric taxonomy, and the policy that keeps it from decaying. Lead incident response from detection through containment, root cause, postmortem, and the structural fix. Support hosted and customer-controlled deployment patterns while keeping the operational model consistent and auditable. Travel to customer sites when working alongside a customer’s engineering or security team will materially improve a deployment or incident outcome. The environment you will work in Our current infrastructure environment includes GCP, Kubernetes and GKE, Knative, Envoy, Cloudflare, Pulumi, Helm, BuildKit, PostgreSQL and Cloud SQL, object storage, container registries, workload identity, Python and Go control-plane services, Kubernetes operators, GitHub Actions, and production observability. Alert triage is substantially agent-driven, with automated investigation, ticket filing, and a decay process that nominates monitors nobody has acted on for deletion. We also support customer-controlled deployment requirements and maintain more than one application-serving path during platform migrations. This is context, not a checklist. We do not require previous experience with every cloud product or tool. We care about deep systems fundamentals, the ability to learn unfamiliar infrastructure, and evidence that you have personally operated and recovered important multi-tenant systems. What we are looking for 5-12 years of software or infrastructure engineering experience. We will make exceptions for exceptional people in either direction. Experience building production control-plane software, operators, platform services, or developer infrastructure, not only configuring vendor products. Experience with infrastructure-as-code and delivery systems, including state management, drift detection, reproducible builds, staged rollout, and rollback. Evidence of owning consequential production systems through incidents, capacity changes, recovery exercises, and reliability improvements. A security-minded approach to tenant isolation, credentials, access control, software supply chains, and customer data. The ability to write maintainable production software and automated tests for infrastructure behavior. AI-native. You use coding agents and modern models as a force multiplier while still understanding and owning every critical operational decision. Clear communication and high EQ. You can work with a customer’s CTO, security team, and infrastructure engineers without losing technical depth. Comfort with startup ambiguity, broad ownership, and occasional customer travel. Deep PostgreSQL expertise is a strong signal for the data platform: connection management and pooling, query planning and indexing, online schema change, and multi-tenant isolation as an enforced guarantee rather than an application convention. So is Kubernetes performance and capacity depth for the reliability work, along with incident command experience and postmortems that produce structural change rather than an action item nobody does. We do not expect all of it from one person. Engineers from Kubernetes platforms, managed databases, cloud networking and identity, developer environments, sandbox systems, PaaS/serverless infrastructure, delivery platforms, and systems-oriented SRE teams often do well here. We care more about what you personally built, operated, and recovered than a particular school or vendor certification. Interview process A 30-minute introductory conversation. Two 60-minute technical interviews, one focused on systems design and one on coding. A take-home assignment where you build and present a real solution using the tools you would use on the job. Why join Build the secure execution foundation for agents doing real work in large enterprises. Solve systems problems spanning Kubernetes, control planes, identity, networking, data, delivery, and recovery. Turn difficult customer deployment constraints into a platform that scales across environments. Work on infrastructure where software design and operational judgment matter equally. Join early enough to define how the engineering team operates and grows. Receive competitive cash compensation and meaningful equity in the company you are helping build. Hard problems, real impact Trust architectures, memory systems, multi-agent coordination. The foundational layer that makes AI agents work in production. Small team, high ownership Every engineer shapes the product and the culture. No layers of process between you and the work that matters. Backed by the best $65M from Coatue, Lightspeed, Abstract Ventures, Dell Technologies Capital, 8VC, and notable industry angels. Grow with us Competitive compensation, meaningful equity, and a genuine focus on your growth as the company scales. Apply for this role Interested in this position? Fill out the form below and we'll be in touch. Name Email LinkedIn GitHub (optional) Message (optional) Resume / Cover Letter (optional) Drag & drop your file here, or click to browse PDF, MD, HTML, up to 25 MB apply now apply now COMPANY HOME ABOUT LABS CAREERS CONTACT RESOURCES BLOG BRAND PRESS LLMS.TXT STATUS UP POLICIES PRIVACY TERMS COOKIES BUG BOUNTY TRUST CENTER © 2026 SYCAMORE LABS, INC. MADE WITH BY SYCAMORE

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

Engineering

125 days ago

Cloud Platform Engineer

Sycamore · Palo Alto, California

Pay

$115k–180k

Setting

On-site

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

Engineering

125 days ago

Staff Software Engineer

Sycamore · Palo Alto, California

Pay

$150k–250k

Setting

On-site

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

Engineering

125 days ago

Applied AI Engineer

Sycamore · Palo Alto, California

Pay

$140k–230k

Setting

On-site

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This website uses cookies We use cookies to personalise content and ads, to provide social media features and to analyse our traffic. We also share information about your use of our site with our social media, advertising and analytics partners who may combine it with other information that you’ve provided to them or that they’ve collected from your use of their services. Show details Allow all Deny Skip to content home about labs careers contact human agent join the waitlist join the waitlist ← Careers Member of Technical Staff, Applied AI Applied AI · Palo Alto · Full-Time Build with enterprise customers, own the path to production, and turn repeated lessons into a better product. About Sycamore Sycamore is building the trusted agent operating system for the enterprise. Our platform helps companies build, deploy, and orchestrate AI agents that take on real operational work, with the security and control large organizations need. We are a small, engineering-led team working directly with Fortune 500 enterprises. We have raised $65M from Coatue and Lightspeed, along with other investors and industry leaders. The role The simplest way to describe this role: you are the engineer in the customer room and the product engineer who ships what the room needs. You will map how an important workflow works today, find where an agent can create a measurable outcome, and build the application end to end, from the user experience and data model through agent tools, integrations, permissions, approval points, and the operational controls needed to run safely. You own the full loop: discovery, implementation, realistic testing, deployment, production debugging, adoption, and iteration. Customer-specific product work belongs with you, and when the same runtime, connector, memory, or deployment need appears repeatedly, you work with Core AI or Infrastructure to turn it into a reusable capability rather than maintaining parallel custom implementations. What you will do Turn ambiguous enterprise problems into clear technical designs, working software, and measurable outcomes. Build product surfaces for agent conversations, tasks, progress, approvals, artifacts, and operational workflows. Design APIs and relational data models that accurately represent the customer’s domain and remain understandable as the product evolves. Build agent instructions, tool interfaces, connector interactions, and durable workflow steps with explicit permission and failure behavior. Navigate enterprise requirements around authentication, authorization, tenant isolation, data handling, deployment, observability, and change management. Test realistic user journeys rather than stopping at isolated units or happy-path demos. Travel to customer sites when working alongside users will accelerate discovery, delivery, or adoption. The environment you will work in Our current product environment includes TypeScript, React, TanStack, Tailwind, Python, FastAPI, typed data models, PostgreSQL, durable workflows, MCP-based tools and connectors, browser automation, and cloud-native deployment on Kubernetes. We use automated tests, coding agents, traces, evaluations, and production feedback as part of everyday engineering. This is context, not a checklist. We do not require previous experience with every language, framework, or vendor in our stack. Strong engineers who understand systems, learn quickly, and have shipped production software can become effective here without matching our tools one for one. What we are looking for 5-12 years of software engineering experience. We will make exceptions for exceptional people in either direction. Strong software fundamentals across product design, APIs, data modeling, distributed systems, testing, and production debugging. Evidence that you personally shipped and operated meaningful software, rather than stopping at prototypes or delegating the production work. Product judgment. You can find the real problem behind a request, choose a useful first version, and decide what should remain customer-specific versus become reusable. Comfort moving across user interfaces, backend services, data, agent behavior, integrations, and deployment when the outcome requires it. A security-minded approach to enterprise data, permissions, credentials, approvals, and auditability. AI-native. You use coding agents and modern models as a force multiplier while still owning the architecture, understanding the code, and explaining important decisions. Clear communication and high EQ. You can work with a customer’s CTO, operators, security team, and engineers without losing technical depth. Comfort with startup ambiguity, fast feedback loops, broad ownership, and regular customer travel. Former founders, early product engineers, and forward-deployed engineers often do well in this role when they have retained real code and production ownership. That background is a signal, not a requirement. What this role is not It is not a pre-sales role that stops at a demo or architecture diagram. It is not a solutions role that hands requirements to another engineering team. It is not an ML research role focused on training foundation models. It is not a narrow role defined by one programming language or layer of the stack. It is not custom development without product judgment; repeated needs should improve the platform. Interview process A 30-minute introductory conversation. Two 60-minute technical interviews, one focused on systems design and one on coding. A take-home assignment where you build and present a real solution using the tools you would use on the job. Why join Work on AI systems that move from enterprise problems to production outcomes quickly. Own the complete path from workflow discovery through adoption. Shape both individual deployments and the product used across customers. Join early enough to define how the engineering team operates and grows. Receive competitive cash compensation and meaningful equity in the company you are helping build. Hard problems, real impact Trust architectures, memory systems, multi-agent coordination. The foundational layer that makes AI agents work in production. Small team, high ownership Every engineer shapes the product and the culture. No layers of process between you and the work that matters. Backed by the best $65M from Coatue, Lightspeed, Abstract Ventures, Dell Technologies Capital, 8VC, and notable industry angels. Grow with us Competitive compensation, meaningful equity, and a genuine focus on your growth as the company scales. Apply for this role Interested in this position? Fill out the form below and we'll be in touch. Name Email LinkedIn GitHub (optional) Message (optional) Resume / Cover Letter (optional) Drag & drop your file here, or click to browse PDF, MD, HTML, up to 25 MB apply now apply now COMPANY HOME ABOUT LABS CAREERS CONTACT RESOURCES BLOG BRAND PRESS LLMS.TXT STATUS UP POLICIES PRIVACY TERMS COOKIES BUG BOUNTY TRUST CENTER © 2026 SYCAMORE LABS, INC. MADE WITH BY SYCAMORE

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

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