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Senior AI Engineer

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Onsite

Senior AI Engineer

Fieldguide

Senior AI Engineer

Skills

TypescriptPythonPostgreSQLAICompliance

2 months ago

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Important information


Contract type:

Permanent

Salary:

$190,000 – $255,000 / year

Location:

United States

Work mode:

Onsite

Published on:

29 August 2026

What they need


  • 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
  • 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
  • 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
  • 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
  • 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
  • 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

Benefits

  • Health
  • Dental
  • PTO- Bias to building: You move fast and resolve uncertainty by shipping
  • 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
  • AI-native instincts: You treat LLMs, agents, and automation as core building blocks
  • You’re a strong software engineer who’s built your skills for an AI-native world. These principles resonate with you:
  • 3–6+ years shipping production software in complex, real-world systems
  • 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
  • We care more about capability and trajectory than years on a resume, but most strong candidates have:
  • Implemented evaluation frameworks for model outputs and agent behavior
  • Strong command of TypeScript, Python, and Postgres
  • Built retrieval pipelines and agent orchestration systems
  • Shipped LLM-powered features serving real production traffic

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