Backend Engineer, AI SRE

Kloudfuse; Cupertino, Northern (CA, KY); Hybride; USD 150 000 - 230 000; Plein temps

Résumé du poste

Kloudfuse is building an agent fleet that investigates live production incidents, orchestrating multi-agent loops and handoffs, with real telemetry and KPIs to evaluate outcomes.

You will wire agents to observability data via MCP tools, shape guardrails, and ensure safe autonomous operation in production environments. We ship first, then iterate, with hands-on ownership from week one.

Qualifications

• Backend engineering experience in distributed systems.
• Experience building agentic systems with multi-step planning.
• Ability to assess autonomy and safety in unattended operations.
• Experience reasoning about production incidents.

Responsabilités

• Build the agent fleet that investigates live production incidents.
• Design multi-agent orchestration and handoffs between agents.
• Wire agents to observability data through MCP tools and telemetry sources.
• Build evaluation harnesses to measure correctness of investigations.
• Ship guardrails with least-privilege tool surfaces and permission models.

Connaissances

Backend engineering

Distributed systems

Agentic systems

SRE awareness

Outils

MCP tools

Observability data

Description du poste

Build the agent fleet that investigates live production incidents, and the guardrails that make it safe to run.

What you’ll work on

• Build the agent fleet that investigates live production incidents: gathering context, forming hypotheses, testing them against real telemetry, and synthesising a root cause.
• Design multi-agent orchestration: coordinator loops, specialised sub-agents, and the handoffs between them.
• Wire agents to real observability data through MCP tools: metrics, logs, traces, Kubernetes state, profiles.
• Build the evaluation harnesses that tell us whether an investigation was actually correct, not merely plausible.
• Ship guardrails: least-privilege tool surfaces, read-only boundaries, and permission models that hold under autonomous operation.

What we look for

• Strong backend engineering first. This is distributed systems work that happens to involve LLMs, not prompt-tuning.
• Experience building agentic systems: tool use, function calling, multi-step planning, long-running loops.
• Judgment about autonomy and safety: what an agent should do unattended, and what it must never do.
• Ability to reason about production incidents yourself. You can’t build an SRE agent without SRE instincts.

Bonus

• SRE, on-call or incident-response background. You’ve been paged and know what a real investigation feels like.
• Observability depth: correlating metrics, logs and traces to isolate a failure.
• Experience with agent SDKs, MCP, or building tools for LLMs to consume.
• Eval tooling and LLM-as-judge methods, and a healthy scepticism about both.
• Prompts-as-code discipline: versioned, reviewed and tested like any other source.

How we work

• Small team, short feedback loops, real ownership from week one.
• You’ll talk to customers, engineers debugging real incidents, and that shapes what you build.
• We ship, then iterate; bias toward hands-on building over process.
• Modern tooling is encouraged, including AI-assisted development.