Hybrid AI Engineer, All Levels

at Fieldguide

• Job title: AI Engineer, All Levels
• Job type: Full Time
• Experience level: Junior, Mid level
• Salary: $170,000 - $310,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: Postgres, Python, React, TypeScript
• Location requirements: Hybrid, San Francisco, United States

About the role

• AI Engineer designing and building agentic systems for audit workflows. Collaborating closely with product and design teams in a hybrid work environment.

Responsibilities

• Design, build, and ship agentic systems that automate and augment complex audit workflows
• Translate customer problems into concrete agent behaviors and workflows
• Integrate and orchestrate LLMs, tools, retrieval systems, and logic into cohesive, reliable agent experiences
• Own agents in production, including performance and observability
• Use AI as core leverage in how you design, build, test, and iterate
• Prototype quickly to resolve uncertainty, then harden systems for enterprise-grade reliability
• Build evaluations, feedback mechanisms, and guardrails so agents improve over time
• Design prompts, retrieval pipelines, and agent orchestration systems that perform reliably at scale
• Make tradeoffs about what to build, what to cut, and what not to build at all
• Partner closely with Product and Design to define agent capabilities that drive real customer outcomes
• Stay deeply connected to how customers actually use agents and optimize for the highest impact problems
• Identify the highest-leverage capability gaps and unblock them without waiting for direction
• Take full ownership of large product areas rather than executing on narrow tasks
• Identify bottlenecks and unblock progress without waiting for direction
• Increase team velocity by building reusable abstractions, tools, and patterns for agent development

Requirements

• Multiple years of experience shipping production software in complex, real-world systems
• Experience with TypeScript, React, Python, and Postgres
• Built and deployed LLM-powered features serving production traffic
• Designed retrieval pipelines and agent orchestration systems
• Implemented evaluation frameworks for model outputs and agent behaviors
• Worked with vector databases, embedding models, and RAG architectures
• Hands-on experience with modern LLM APIs (OpenAI, Gemini, Anthropic, etc.) and agent frameworks
• Comfort operating in ambiguity and taking responsibility for outcomes
• Deep empathy for professional-grade, mission-critical software (experience with audit and accounting workflows are not required)

Benefits

• Competitive compensation packages with equity ownership
• 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.