- Company Name
- Fieldguide
- Job Title
- AI Engineer (All Levels)
- Job Description
-
Job title: AI Engineer (All Levels)
Role Summary:
Design, build, and ship AI agents that automate complex audit and advisory workflows. Own end‑to‑end agent development, from translating user problems into behavior, integrating LLMs and retrieval systems, to ensuring production reliability, observability, and continuous improvement.
Expectations:
• All seniority levels; seniority calibrated during interview based on background and desired ownership.
• Fast, production‑grade software delivery with strong product judgment.
• Deep learning velocity, bias toward building, and end‑to‑end ownership of large product areas.
Key Responsibilities:
- Build and deploy agentic systems that automate audit workflows.
- Translate customer problems into concrete agent behaviors and workflows.
- Integrate and orchestrate LLMs, tools, retrieval pipelines, and logic into reliable, scalable agent experiences.
- Own agents in production: monitor performance, observability, and reliability.
- Prototype rapidly, harden systems, and implement evaluation frameworks, guardrails, and feedback mechanisms for continual improvement.
- Design prompts, retrieval pipelines, and agent orchestration at enterprise scale.
- Make product trade‑offs and collaborate closely with Product and Design to deliver high‑impact capabilities.
- Identify bottlenecks, build reusable abstractions, tools, and patterns to increase team velocity.
Required Skills:
- Proven experience shipping production software in complex systems.
- Strong background in TypeScript, Python, React, and PostgreSQL.
- Built and deployed LLM‑powered features handling production traffic.
- Designed retrieval pipelines and agent orchestration systems.
- Implemented evaluation frameworks for model outputs and agent behaviors.
- Hands‑on with vector databases, embedding models, and RAG architectures.
- Proficiency with modern LLM APIs (OpenAI, Gemini, Anthropic, etc.) and agent frameworks.
- Ability to operate in ambiguity, take responsibility for outcomes, and maintain professional‑grade, mission‑critical software standards.
Required Education & Certifications:
- Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
- No specific certifications required; relevant AI/ML or software engineering certifications are a plus.
San francisco, United states
Hybrid
07-01-2026