Senior Infrastructure Engineer

Who you are

You are an experienced Infrastructure Engineer Engineer who owns backend infrastructure end to end. You design multi-tenant, microservices-based systems that other engineering teams build on, and you make deliberate architectural tradeoffs around consistency, latency, scale, and cost. You are comfortable going deep — service mesh internals, database internals, distributed-systems failure modes — and equally comfortable defining the reliability and security contracts an enterprise AI platform depends on.

Responsibilities

• Design, own, and evolve scalable microservices architectures on Kubernetes across GCP, Azure, and AWS, including multi-tenant isolation (namespaces, network policies, per-tenant resource quotas and RBAC).
• Build core platform and data-plane components in Golang and Python — data ingestion, knowledge-base indexing and vector/graph search, application connectivity, workflow automation, and ML operations — against explicit latency and throughput SLOs.
• Own service-to-service communication: gRPC/protobuf API contracts, service mesh (Istio/Linkerd), load balancing, retries, timeouts, and circuit breaking.
• Make and document architectural tradeoffs — partitioning/sharding strategy, consistency models (strong vs. eventual), caching tiers, and build-vs-buy decisions.
• Define the reliability contract: SLIs/SLOs, error budgets, capacity planning, autoscaling (HPA/VPA/KEDA), and graceful degradation.
• Design and operate the observability stack — Prometheus, Grafana, OpenTelemetry, distributed tracing, and real-time alerting — for full visibility into system health.
• Drive DevOps and platform-engineering practices: IaC (Terraform), Helm, GitOps (ArgoCD/Flux), and CI/CD pipelines.
• Optimize for performance and cost — profiling, load testing, latency budgets, and cost-per-request.
• Participate in on-call rotations and lead incident response and root-cause analysis.

Qualifications

• Bachelor's degree in Computer Science or a related field.
• 5+ years of experience in Platform, Infrastructure, or Backend Engineering.
• Strong CS fundamentals: data structures, algorithms, operating systems, and networking.
• Proficiency in Golang and Python.
• Production experience with Docker, Kubernetes, and microservices architecture.
• Hands-on experience with at least one major cloud provider (GCP, Azure, or AWS); multi-cloud a strong plus.
• Strong database expertise: query and read/write-path optimization, partitioning/sharding, replication and consistency models, with practical experience in NoSQL and graph stores. Solid grasp of the CAP theorem and database internals.
• Solid distributed-systems foundation: idempotency, backpressure, delivery semantics (at-least-once vs. exactly-once), and message queues (Kafka/Pulsar/NATS/PubSub).
• Track record of building platforms from the ground up that other engineering teams successfully build on.

Bonus

• Experience operating systems at high scale (high QPS, large data volumes).
• Depth in auth and security: secrets management (Vault), mTLS, RBAC, OIDC/SAML, network policy.
• Experience with vector databases (pgvector/Pinecone/Milvus) and graph databases (Neo4j/Neptune).
• Open-source contributions to infrastructure projects (e.g., Kubernetes operators).

Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.