AI Engineer

COMO is building the future of cyber resilience. Our AI-native platform helps organizations understand their ability to recover from cyberattacks, identify critical gaps and dependencies, and prepare for what happens after an attack. Backed by a significant seed round led by General Catalyst, with a live product and paying customers, we're building an exceptional team to define a new category in cybersecurity.

We're hiring our first AI Engineer. AI agents are at the core of how COMO works: they analyze customer environments, decide what matters, and turn raw signals into findings security teams act on. You'll be the engineer who builds them. You'll take the foundations we have today and turn them into a production-grade agents platform, then design and ship the agents that run on it, with real customers using your work within weeks. This is a hands-on engineering role for someone who builds agents, not a data science or research position.

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  Build and own our agents platform: a common runtime with typed outputs, reproducibility, evals and guardrails, cost and latency budgets, and a full audit trail

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  Design and ship production agents: triage, classification, prioritization, and enrichment of what we know about each customer environment

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  Own agent quality as a number: offline and online evals that catch regressions before customers do

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  Take agents into real customer environments and use what you learn to set the roadmap

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  Work directly with the founders and the engineers behind our data pipelines

• 5+ years of experience in a Software Engineering role, including 2+ years as an AI Engineer building LLM-based systems and agents in production

• Hands-on experience designing and shipping agents (tool use, orchestration, structured outputs) with real users, not demos

• Experience with eval-driven development: offline and online evals, measuring quality regressions, and numbers to show for it

• Strong backend fundamentals in any major language (ours is Python)

• Hands-on experience with LLM APIs (Bedrock, OpenAI, or Anthropic) in production, including cost and latency budgeting

• Security, infrastructure, or observability background - advantage

• Early-stage startup experience - advantage

Python, AWS Bedrock, Kafka, PostgreSQL, Polars, Nx monorepo, with an AI-native workflow throughout.