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Sr Backend Engineer - AI

Roles & Responsibilities

  • 5-8 years building backend systems in production
  • Strong with Go and async Python (FastAPI, Pydantic, asyncio)
  • Experience building distributed systems while writing clean and scalable code
  • Ability to drive initiatives end-to-end

Requirements:

  • Work on Noz, the AI teammate: agent orchestration, tool execution, and APIs streaming results
  • Develop SigNoz MCP server for observability data exposure to LLM agents
  • Manage the hard parts of agent backends: execution, security, streaming over SSE
  • Implement LLM/GenAI observability for monitoring AI apps with OpenTelemetry

Job description

About SigNoz

SigNoz is an open-source observability platform that helps modern engineering teams monitor, debug, and optimize their applications with deep visibility into metrics, traces, and logs, all in one place. We're built natively on OpenTelemetry and offer both self-hosted and cloud options, so teams can run observability the way they want, without vendor lock-in.

We are growing fast and building core developer infra products. And we are not fooling around:

  • 27,000+ GitHub stars

  • 900+ customers

  • 8,000+ members in our Slack community

Role: Sr Backend Engineer - AI

We're looking for a Sr Backend Engineer for Nerve team, our AI pod. Nerve team builds the AI layer of SigNoz: Noz (observability AI teammate inside SigNoz), the SigNoz MCP server, AI SRE, and LLM/GenAI observability. We're building agent-native observability at SigNoz, where the engineer and their agent are both first-class users.

What you'll work on

You will be working with the high-caliber team in some of the below areas.

  • Noz, AI teammate: agent orchestration, tool execution, and the APIs that stream results back into the product

  • SigNoz MCP server that exposes observability data to LLM agents, so any agent can query a user's logs, metrics, and traces

  • The hard parts of agent backends: long-running execution, security, streaming over SSE, tool calling, and session state across DBs

  • LLM/GenAI observability, so teams (including us) can monitor their own AI apps with OpenTelemetry

What will make you successful

  • 5-8 years building backend systems in production. You'll work across both Go and Python.

  • Strong with Go (concurrency, channels, performance) and with async Python (FastAPI, Pydantic, asyncio), and comfortable designing APIs and data models.

  • You have built and shipped LLM features in production: agents, tool or function calling, evals, MCP, context and prompt engineering. You know how to make a non-deterministic system behave like a dependable one.

  • Experience building distributed systems while writing clean and scalable code

  • Ability to drive initiatives end-to-end: from problem discovery → design → implementation → rollout

  • Comfortable working in a high-ownership, fast-moving, remote-first environment

  • Strong communication skills, can write clear tech docs and explain trade-offs

Nice-to-haves

  • Past experience in AI or platform teams of series B+ startups

  • Experience in observability (monitoring / logging / tracing)

  • Familiarity with OpenTelemetry and/or ClickHouse, Kafka, Kubernetes, etc.

  • Loves open source, ideally with prior contributions to OSS projects (any size)

Why you'll love working at SigNoz

  • You'll help define agent-native observability, a new category, not maintain a mature dashboard product.

  • Work on a globally used open-source project that engineers actually love

  • Collaborate with high-caliber team who just can't stop shipping

  • Remote-first, async-friendly culture

  • Opportunity to help define the future of open-source observability

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