Offensive security services from human-led to autonomous pentesting. Identify exposures, get ahead of threats, and maintain compliance—fast and precise. Backed by 500 Global and Alchemist.
About the role
Cobalt runs AI agents in production that test real customer applications. We’re looking for a Staff AI Engineer who has built and operated production agent systems and can help us make them more reliable, secure and cost-efficient. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Significant software engineering experience, typically 8–10+ years, with a track record of technical leadership across teams
- Hands-on experience building and operating LLM-based agents in production, with a clear understanding of their scale, constraints and business outcomes
- A track record of improving agent reliability: building evaluations, investigating non-deterministic failures and improving success rates against measurable goals
- Strong knowledge of agent architectures, including tool use, orchestration, planning, context and memory management, and the judgment to know when simpler workflows are sufficient
- Experience running LLM workloads through managed cloud model platforms or direct provider APIs, including rate limits, failure handling and cost tracking
- Strong backend and distributed systems fundamentals, including APIs, asynchronous workflows, concurrency and fault tolerance
More about this role
Cobalt runs AI agents in production that test real customer applications. We’re looking for a Staff AI Engineer who has built and operated production agent systems and can help us make them more reliable, secure and cost-efficient.
You’ll set the technical direction for how we design, evaluate, ship and operate agents, and stay hands-on building the foundations our teams use. You’ll work across engineering, product, research and security, mentoring engineers and helping teams turn promising prototypes into dependable production systems.
Your primary focus will be our agent platform and production practices. You’ll also help engineering teams improve how they build software with AI coding agents.
- Set technical direction for agent systems across teams, including orchestration, tool use, context and memory management, human oversight and failure recovery.
- Design, build and operate shared foundations: evaluation frameworks, agent observability and tracing, execution controls, and model access with routing and failover where needed.
- Establish evaluation practices that measure task completion, accuracy, false positives, security and cost per successful task. Work with domain...
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