Staff AI Engineer

Job not on LinkedIn

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $200k - $240k / year

⏰ Full Time

🔴 Lead

🤖 AI Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 1%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Cobalt

WebsiteLinkedInAll Job Openings

201 - 500 employees

🔐 Security

☁️ SaaS

Security • SaaS

Cobalt is a leading provider of offensive security services, specializing in modern pentesting solutions. They offer a comprehensive platform that includes dynamic application security testing, network security, and cloud security. Known as the pioneers of Pentest as a Service (PtaaS), Cobalt allows organizations to efficiently scale their security efforts with on-demand access to a pool of expert pentesters. Their services are designed to help businesses identify risks and secure their infrastructure efficiently while ensuring compliance with industry standards. Cobalt's innovative approach and proven experience help companies reduce security risks and improve their overall security posture.

📋 Description

• 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 for evaluations, observability, tracing, execution controls and model access with routing and failover • Establish evaluation practices for task completion, accuracy, false positives, security and cost per successful task • Build representative test cases with domain experts and turn production failures into regression tests • Improve resilience to tool failures, timeouts, rate limits and partial execution with limits on retries, runtime and spend • Build scoped permissions, customer data isolation, audit trails and safe tool/code execution with security and platform teams • Establish engineering standards for CI evaluations, prompt/model versioning, regression testing, cost and latency budgets, and staged rollouts • Lead model selection and cost optimization by benchmarking models against real workloads • Partner with teams on production readiness, incident investigation and agent reliability • Help engineering teams use AI coding agents across planning, implementation, review and testing • Mentor engineers and technical leads through design reviews, pairing, internal talks and written guidance • Create a technical roadmap with product, research and security leaders

🎯 Requirements

• 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 • Track record of improving agent reliability through evaluations, non-deterministic failure investigation and measurable success-rate improvements • Strong knowledge of agent architectures, including tool use, orchestration, planning, context and memory management • 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 • Understanding of security risks in agent systems, including prompt injection, unsafe tool execution and sensitive-data exposure • Evidence of impact beyond individual code, such as shared platforms, improved standards or mentoring engineers • Experience with agent orchestration, tool calling and structured outputs • Experience with Model Context Protocol (MCP), APIs and permission-controlled tool execution • Experience with automated evaluation harnesses, domain-specific test datasets and regression testing in CI • Experience with distributed tracing, structured logs and metrics for multi-step agent workflows • Experience with managed cloud model platforms, direct provider APIs and multi-provider gateways

🏖️ Benefits

• Competitive compensation and an attractive equity plan • 401(k) program (US) or pension (EU) • Medical, dental, vision and life insurance (US) or statutory healthcare (EU) • Wellness stipend • Work-from-home equipment and Wi-Fi stipend • Learning and development stipend • Flexible, generous paid time off • Paid parental leave • Ongoing mentorship opportunities