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FieldguideFieldguideSan Francisco, CA

Senior AI Engineer

Builds and ships AI agents that automate complex audit workflows using LLMs, retrieval pipelines, and orchestration logic. Owns end-to-end development, evaluation, reliability, and mentoring while partnering with product and design teams. Requires 3+ years experience with production LLM features.

190k – 255k
Hybrid3+ YOEML Engineering

About the role

What You’ll Own

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

Who You Are

Strong software engineer with bias to building, AI-native instincts, strong product judgment, learning velocity, grounded optimism, and end-to-end ownership.

Experience

  • 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.
  • Wellness benefits starting on your first day

Skills

TypeScriptPythonPostgresLLMsOpenAIGeminiAnthropicRAGVector DatabasesEmbedding ModelsAgent FrameworksRetrieval PipelinesAgent OrchestrationEvaluation Frameworks

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