Engineering Lead, Agents

Responsibilities

• Provide technical leadership across the agent platform
• Design and build agent-driven workflows and internal systems
• Build eval, observability, and feedback systems that improve agent reliability, performance, and learning over time
• Establish patterns and infrastructure for reliable agent deployment

Requirements

• 3+ years building software at a frontier AI lab, agentic startup, leading hedge fund, big tech company, or similar
• Strong familiarity with the modern AI stack (LLMs, tool use, orchestration, evaluation)
• Proficiency in Python and SQL, with bonus for TypeScript, Go, or Rust
• Basic understanding of financial markets and a personal or professional interest in investing
• Demonstrated experience designing, building, and deploying multi-agent systems in production environments; expertise in agent orchestration, tool calling, context window management, and agent grounding
• Proven ability to anticipate and address failure modes, with hands-on experience in observability and evaluation of agent systems
• BS/MS/PhD in Computer Science or related field, or equivalent practical experience

Qualifications

• Familiarity with agent safety, sandboxing, and guardrail design for high-stakes environments
• Experience working directly with researchers or quantitative developers as a technical partner
• Experience working with unstructured financial data (filings, earnings transcripts, news) and financial data providers (Bloomberg, CapitalIQ, Refinitiv)

Skills

• Technical leadership
• Software engineering
• AI and machine learning
• Financial markets

Benefits

• Adequate medical, dental, and vision coverage
• Catered lunches in our Menlo Park office
• Commuter benefits

Pay

$180K - $280K

Schedule

Hybrid: 3 days per week on-site at our office in Menlo Park, CA. Relocation allowance available.