Senior AI Engineer

About the Role

Fieldguide is building AI agents for the most complex audit and advisory workflows. As a Senior AI Engineer, you'll own meaningful product areas end-to-end—designing agentic architectures, building evaluation systems, and shipping agents that professionals trust with mission-critical work.

This role is for engineers who have shipped LLM-powered features in production and are ready to take the lead on complex systems while mentoring those around them.

What You’ll OwnBuild 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

Who You Are

You’re a strong software engineer who’s built your skills for an AI-native world. These principles resonate with you:

• Bias to building: You move fast and resolve uncertainty by shipping
• AI-native instincts: You treat LLMs, agents, and automation as core building blocks
• Strong product judgment: You decide what matters and why—not just how to implement it
• Learning velocity: You learn quickly from feedback and adjust based on data
• Grounded optimism: You improve what's broken today and push toward what's possible next
• End-to-end ownership: You understand production systems and own outcomes

ExperienceWe care more about capability and trajectory than years on a resume, but most strong candidates have:

• 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

What Should Excite You

• Enterprise-grade reliability: Building systems professionals depend on
• Human-in-the-loop design: Knowing when to automate vs. when to surface decisions
• Nuanced evaluation: Audits require judgment, so feedback structures matter
• Explainability: Making AI outputs and reasoning transparent and trustworthy
• Complex domains: Navigating compliance and enterprise rigor while moving fast
• Shipping daily value: Delivering agent experiences customers use every day