Hybrid Senior AI Engineer

at Fieldguide

• Job title: Senior AI Engineer
• Job type: Full Time
• Experience level: Senior
• Salary: $190,000 - $240,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: Postgres, Python, TypeScript
• Location requirements: Hybrid, San Francisco, United States

About the role

• Senior AI Engineer designing and building agentic systems that automate complex audit workflows for Fieldguide. Leading technical projects and mentoring team members while delivering high-impact results.

Responsibilities

• Build and Ship AI Agents
• Design and build agentic systems that automate complex audit workflows end-to-end
• Translate customer problems into concrete agent behaviors and orchestration logic
• Orchestrate LLMs, tools, retrieval, and business logic into reliable, production-grade agent experiences
• Own agents across their lifecycle: delivery, reliability, performance, and observability
• Execute with AI-Native Leverage
• Use AI to accelerate design, build, test, and iteration cycles
• Prototype quickly, then harden systems for enterprise-grade reliability
• Build evaluation frameworks, feedback loops, and guardrails to improve agents over time
• Design prompts, retrieval pipelines, and orchestration logic that perform at scale
• Drive Product Impact
• Make clear trade-offs on what to build, cut, or skip based on customer value
• Partner with Product and Design to define capabilities that deliver real outcomes
• Stay close to customer workflows and optimize for highest-impact problems
• Identify capability gaps and unblock team progress proactively
• Mentor and Multiply the Team
• Raise the quality bar through code review, design feedback, and pairing
• Create reusable abstractions, patterns, and tooling that increase team velocity
• Share learnings across the team and establish engineering best practices

Requirements

• 3–6+ years shipping production software in complex, real-world systems
• Strong command of TypeScript, Python, and Postgres
• Shipped LLM-powered features serving real production traffic
• Built retrieval pipelines and agent orchestration systems
• Implemented evaluation frameworks for model outputs and agent behavior
• Worked with vector databases, embedding models, and RAG architectures
• Hands-on experience with modern LLM APIs (OpenAI, Gemini, Anthropic) and agent frameworks
• Comfortable operating in ambiguity and taking responsibility for outcomes

Benefits

• Competitive compensation with equity
• Comprehensive health and wellness benefits
• Flexible time off and work schedules
• Technology reimbursements
• 401(k) plan
• Twice-yearly in-person offsites across the U.S.