Backend Engineer, AI SRE

Kloudfuse; Cupertino (CA); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Blumberg Capital Company is seeking a skilled backend engineer to join our engineering team in Cupertino or remote. You will build the agent fleet that investigates live production incidents, design multi-agent orchestration, and wire agents to observability data.

You’ll work on guardrails, evaluation harnesses, and modern tooling while shipping production-grade systems that operate with autonomy and safety in mind.

Qualifications

• Strong backend engineering background in distributed systems.
• Experience building agentic systems with tool use, function calling, multi-step planning and long-running loops.
• Judgment about autonomy and safety in unattended agent behavior.
• Ability to reason about production incidents with SRE instincts.

Responsibilities

• Build the agent fleet that investigates live production incidents: gathering context, forming hypotheses, testing against telemetry, and synthesising a root cause.
• Design multi-agent orchestration: coordinator loops, specialised sub-agents, and handoffs between them.
• Wire agents to real observability data through MCP tools: metrics, logs, traces, Kubernetes state, profiles.
• Build evaluation harnesses to determine true correctness of investigations.
• Ship guardrails: least-privilege surfaces, read-only boundaries, and strict permission models for autonomous operation.

Skills

Agentic systems

Tool use

Function calling

Multi-step planning

Long-running loops

Autonomy safety judgment

SRE instincts

Tools

Go

Python

MCP

Kubernetes

Job description

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.

Team

• Engineering

Location

• Cupertino / Remote

Type

• Full‑time

Stack

• Go Python MCP Kubernetes