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W2-Senior Backend Engineer – AI/LLM Agents

Redwood City, California, United StatesHybridContractSeniorPosted 1 month ago

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Job Title-
Senior Backend Engineer – AI/LLM Agents

Work Location:
Redwood City, CA -Hybrid-3 days a week on site

Interview: 2 rounds virtual 1 round in person

Visa:- USC OR Green Card Holder only preferred but any visa is okay(Not H1B)

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.

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.

*Best Regards,*

Jaideep Shastri

916-365-9533 (D) |
jaideep.shastri@fustis.com

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