AI Back End Engineer/Architect (Onsite in Redwood City, CA) In Person Interview

Send Candidates who have strong AI/LLM and backend developer experience

• LLM product experience: prompting, tool calling, evals, latency/cost tradeoffs.
• Agent architectures: planning/execution loops, memory/state, sandboxed tools, HITL, safety constraints.
• Frameworks/SDKs: Vercel AI SDK, LangChain/LangGraph, Anthropic Agents, OpenAI tool calling, sandboxed runtimes.
• Infra familiarity: Kubernetes, serverless, stream processing, feature stores, vector search.

Job Description:

The Role

You ll own the backend systems that make AI agents reliable in production: agent runtime services, integrations, data modeling, observability, and platform reliability. You ll design, ship, measure, and harden systems that power real customer workflows at scale.

What You ll Do

• Own agent runtime services: tool execution, state management, orchestration, retries/idempotency, rate limiting.
• Design APIs & contracts: stable, versioned internal/external APIs, webhooks/events, integration adapters.
• Model complex domain data: schemas for agent memory/state, workflow history, audit trails, permissions, multi-tenant isolation.
• Build integrations at scale: OAuth, webhooks, sync engines, connectors with robust observability and failure handling.
• Reliability engineering: define SLIs/SLOs, implement tracing, timeouts, circuit breakers, budgets, and incident response.
• Performance & cost controls: optimize latency/throughput, queues, caches, storage; manage inference/tool-call costs and runaway tasks.
• Raise the bar: code quality, testing strategy, on-call hygiene, runbooks, postmortems, mentoring.

What We re Looking For (Required)

• 6+ years building backend systems for production SaaS, platforms, or distributed systems.
• Strong fundamentals in distributed systems, concurrency, queues/workers, caching, and production ops.
• Data modeling depth: relational design (Postgres/MySQL), migrations, indexing, query optimization, data correctness.
• API design excellence: clear, evolvable contracts across internal services and external partners.
• Thrive in high-velocity environments without compromising reliability/security.
• Ownership mindset: build ship operate; comfortable with ambiguity and rapid iteration.

• LLM product experience: prompting, tool calling, evals, latency/cost tradeoffs.
• Agent architectures: planning/execution loops, memory/state, sandboxed tools, HITL, safety constraints.
• Frameworks/SDKs: Vercel AI SDK, LangChain/LangGraph, Anthropic Agents, OpenAI tool calling, sandboxed runtimes.
• Infra familiarity: Kubernetes, serverless, stream processing, feature stores, vector search.