Job description
About Us
Fieldguide is a fast-growing enterprise SaaS startup modernizing the audit and advisory industry. We are building AI-powered features to revolutionize how assurance and risk teams work, and we’re seeking a Senior AI Engineer to lead the charge in bringing LLM-driven capabilities into our platform. This is a high-impact role at the intersection of software engineering and applied AI – perfect for someone who loves building production systems with cutting-edge generative AI.
We’re based in San Francisco, CA, but built as a remote-first company that enables you to do your best work from anywhere. We’re backed by top investors including Bessemer Venture Partners, 8VC, Floodgate, Y Combinator, DNX Ventures, Global Founders Capital, Justin Kan, Elad Gil, and more.
We value diversity — in backgrounds and in experiences. We need people from all backgrounds and walks of life to help build the future of audit and advisory. Fieldguide’s team is inclusive, driven, humble and supportive. We are deliberate and self-reflective about the kind of team and culture that we are building, seeking teammates that are not only strong in their own aptitudes but care deeply about supporting each other’s growth.
As an early stage start-up employee, you’ll have the opportunity to build out the future of business trust. We make audit practitioners’ lives easier by eliminating up to 50% of their work and giving them better work-life balance. If you share our values and enthusiasm for building a great culture and product, you will find a home at Fieldguide.
About the Role
As a Senior AI Engineer at Fieldguide, you will architect and implement end-to-end solutions that embed large language models into our core product. You’ll design retrieval-augmented generation workflows, develop AI-driven features that assist our users in real time, and ensure our systems are scalable, reliable, and secure. This role is both hands-on and strategic: you will write and review code, set technical direction for AI initiatives, and establish engineering best practices for production AI systems. If you are excited about prompt engineering, building with LLM APIs, and creating tools that augment human experts, you’ll thrive here.
What You’ll Do
AI Feature Development
Design and build new product features that leverage generative AI, such as co-pilots that assist auditors with document analysis and reporting.
Own the ML feature lifecycle end-to-end – from prototyping prompts and integrations, to backend implementation, deployment, and monitoring.
Ensure AI outputs are accurate, safe, and useful for end users.
Retrieval-Augmented Generation (RAG)
Implement RAG pipelines to ground LLMs in Fieldguide’s domain-specific data.
Integrate and optimize vector databases or embedding stores to enable secure, context-aware AI features.
Blend model outputs with deterministic logic for correctness and reliability.
Prompt Engineering & Tooling
Lead best practices in prompt engineering, template versioning, and structured outputs.
Experiment with agent-style workflows so the AI can call tools, databases, or services safely on behalf of users.
Establish reusable libraries and tooling for consistent and effective AI integrations.
AI System Architecture & Scalability
Design infrastructure to support AI features at scale, balancing performance, reliability, and cost.
Collaborate with infra/DevOps teams on microservices, job queues, caching, and monitoring.
Set up metrics, alerts, and observability for AI-powered services in production.
Evaluation & Continuous Improvement
Define measurable success criteria for AI-driven features (accuracy, relevance, user satisfaction).
Build evaluation pipelines, including automated regression tests and human-in-the-loop reviews.
Use data to refine prompts, retrieval strategies, or model selection, and run A/B tests on improvements.
Collaboration & Leadership
Partner with Product Managers, Designers, and domain experts to translate business problems into AI solutions.
Contribute to UX discussions on how AI insights are presented to users.
Mentor engineers on AI/ML best practices, provide guidance in code reviews, and lead internal knowledge sharing (e.g., AI guilds, training sessions).
Who You Are
5+ years of software engineering experience, including 1+ year building AI/ML-powered features in production.
Strong coding ability in backend languages (Python preferred) and experience with system design for cloud-based services.
Hands-on experience integrating LLM APIs or open-source NLP models into live applications.
Solid understanding of distributed systems, API design, and asynchronous programming.
Familiarity with cloud platforms (AWS or GCP), containers (Docker), and orchestration (Kubernetes).
Practical experience with retrieval-augmented generation, embeddings, and vector databases.
Ability to define and monitor evaluation metrics for AI outputs.
Bonus Points
Experience with MLOps practices: prompt/model versioning, monitoring drift, ensuring reproducibility.
Exposure to fine-tuning, data labeling, or ML workflow tools.
Frontend experience with TypeScript/React for building AI-driven user experiences.
Prior leadership or mentorship experience (tech lead, project lead, or similar).
More about Fieldguide
Fieldguide is a values-based company. Our values are:
Fearless - Inspire & break down seemingly impossible walls.
Fast - Launch fast with excellence, iterate to perfection.
Lovable - Deliver happiness & 11 star experiences.
Owners - Execute & run the business with ownership.
Win-win - Create mutual value & earn trust for life.
Inclusive - Scale the best ideas with inclusive teams.
Some of our benefits include
Competitive compensation packages with meaningful ownership
Flexible PTO
401k
Wellness benefits, including a bundle of free therapy sessions
Technology & Work from Home reimbursement
Flexible work schedules
