Staff AI Engineer, Production Agent Platform Leader

Cobalt; United States; À distance; USD 275 000 - 300 000; Plein temps

Avantages offerts par ce poste

401(k)

Medical, dental, vision insurance

Paid time off

Parental leave

Work-from-home equipment

Résumé du poste

Cobalt is seeking a Staff AI Engineer to lead production agent systems, focusing on reliability, security and cost efficiency. You will set the technical direction for design, evaluation, deployment, and operation of AI agents across teams, while hands-on building foundations used by multiple squads.

You'll mentor engineers, drive production readiness, incident response and measurable improvements in task success, latency and spend, collaborating with product, research and security to align the

Qualifications

• 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.
• Experience with production observability, incident investigation and safe rollout of system changes.
• An understanding of security risks in agent systems, including prompt injection, unsafe tool execution and exposure of sensitive data.
• Evidence of impact beyond your own code: shared platforms other teams adopted, standards that improved outcomes or engineers you helped grow.

Responsabilités

• 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 experts to build representative test cases and turn production failures into regression tests.
• Make agent workflows resilient to tool failures, timeouts, rate limits and partial execution, with clear limits on retries, runtime and spend.
• Work with security and platform teams to build in scoped permissions, customer data isolation, audit trails and safe execution of tools and code.
• Establish practical engineering standards: evals in CI, prompt and model versioning, regression testing for non‑deterministic systems, cost and latency budgets, and staged rollouts with rollback paths.
• Lead model selection and cost optimization. Benchmark models against real workloads and make informed trade‑offs between quality, latency and cost.
• Partner with teams on production readiness, incident investigation and improvements to agent reliability.
• Help teams use AI coding agents effectively across planning, implementation, review and testing. Measure the impact on delivery speed and software quality.
• Mentor engineers and technical leads through design reviews, pairing, internal talks and written guidance. Help teams adopt shared capabilities and improve them based on feedback.
• Work with product, research and security leaders to turn business priorities into a technical roadmap with clear outcomes.

Connaissances

Leadership

Production LLM agents

Agent reliability

Agent architectures

Cloud platforms

Backend systems

Observability

Security awareness

Impact delivery

Outils

Agent orchestration

Tool integration

Evaluations

Observability

Model access

Description du poste

Cobalt is seeking a Staff AI Engineer to lead production agent systems, focusing on reliability, security and cost efficiency. You will set the technical direction for design, evaluation, deployment, and operation of AI agents across teams, while hands-on building foundations used by multiple squads.

You'll mentor engineers, drive production readiness, incident response and measurable improvements in task success, latency and spend, collaborating with product, research and security to align the