F
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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