Infrastructure Engineer
Sycamore
Infrastructure Engineer
Sycamore
Enterprise trusted AI agent operating system
Sycamore is building the trusted agent operating system for the enterprise. Our platform helps companies build, deploy, and orchestrate agentic apps 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.
You will build the infrastructure and control-plane software that lets Sycamore's services, mutable development sandboxes, and immutable deployed applications run securely from development through production.
This is software engineering for consequential distributed systems, not cloud administration. You will write control-plane services and Kubernetes controllers, codify infrastructure and delivery paths, design identity and network boundaries, operate tenant-isolated data systems, and debug failures that cross application, cluster, database, and customer-network layers.
You own more than whether a cluster is healthy or a deployment completed. You own whether the system is isolated, observable, recoverable, cost-aware, and safe to change—and whether the next deployment is more repeatable than the last.
Infrastructure is the foundation beneath Product and Core AI. Errors here can affect every application and customer, so we maintain an especially high bar for systems judgment, production ownership, and recovery discipline.
In one week, you might:
Trace a failed application deployment across artifact creation, image building, registry publication, admission controls, routing, workload identity, health checks, and rollback.
Build or extend a control-plane service or Kubernetes controller that provisions and reconciles tenant or sandbox resources safely.
Design an edge-authentication, service-identity, or delegated-access flow and verify that untrusted workloads cannot cross the boundary.
Investigate latency or reliability across gateways, containers, managed databases, object storage, cluster scheduling, and customer DNS or networks.
Review an infrastructure change for blast radius, execute a staged rollout, watch health signals, and prove the rollback path.
Restore tenant data to a known point, verify the result, and turn the exercise into a repeatable recovery procedure.
Improve sandbox startup time, deployment throughput, resource efficiency, or capacity without weakening isolation.
Work with a customer's infrastructure or security team to satisfy a real deployment constraint, then encode the reusable solution in the platform.
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.
Build deployment systems from versioned artifacts through reproducible image creation, staged rollout, health verification, promotion, and digest-preserving rollback.
Design and debug networking, ingress and edge routing, DNS, TLS, workload identity, secrets, and service-to-service authorization.
Operate tenant-isolated relational databases, object storage, container registries, and deployment metadata.
Own backup, point-in-time recovery, restore verification, regional recovery, capacity planning, and disaster-recovery readiness.
Build observability, SLOs, alerts, capacity controls, and incident-response tooling across clusters, services, sandboxes, and customer workloads.
Maintain production change controls, drift detection, release gates, and fail-safe rollout procedures.
Support hosted and customer-controlled deployment patterns while keeping the operational model consistent and auditable.
Debug complex failures across application code, control planes, containers, Kubernetes, cloud services, databases, identity, and customer networks.
Travel within India when working alongside a customer's engineering or security team will materially improve a deployment or incident outcome.
Our current infrastructure environment includes multiple cloud providers (GCP, AWS, Azure, etc.), 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.
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.
5-12 years of software or infrastructure engineering experience. We will make exceptions for exceptional people in either direction.
Deep hands-on experience with Kubernetes and containers in production, including scheduling, networking, security, deployment, and failure diagnosis.
Strong systems fundamentals across Linux, networking, DNS, TLS, identity, databases, storage, and distributed systems.
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.
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.
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.
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 India engineering team operates and grows.
Work as one engineering team across India and Palo Alto.
Receive competitive cash compensation and meaningful equity in the company you are helping build.
Sycamore Labs builds a trusted agent operating system for enterprises, providing the infrastructure to safely build, deploy, manage, and observe large fleets of AI agents at scale within a secure, governed environment. Its product uses a tiered trust model: new agents begin under heavy supervision and progressively gain autonomy as they prove reliability, with human operators guiding tasks through natural language. The platform focuses on governance, security, observability, and multi-agent coordination to prevent uncoordinated digital chaos and to integrate AI agents with legacy systems. What sets Sycamore apart is its explicit emphasis on trust architectures, centralized oversight, and scalable AI governance, aiming to turn isolated demos into controllable, enterprise-wide automation. The company's goal is to unlock a wave of enterprise automation by enabling AI agents to operate safely and autonomously under policy compliance and security constraints.
Explore more opportunities at Sycamore