REQ AI Back End Engineers

Redwood City, CA - USA

Monthly Salary: Not Disclosed

Posted on: 9 hours ago

Vacancies: 1 Vacancy

Job Summary

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

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

What Youll 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 Were 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.

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...

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

What Youll 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 Were 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.