Sr. Staff Ai/ml Engineer

Gusto · Fintech · Denver, CO +2 · Remote · Data

Sr. Staff AI/ML Engineer responsible for designing, building, and scaling the AI platform that empowers Gusto's internal teams to build intelligent agents and deliver customer value. This includes developing core platform capabilities such as agent orchestration, RAG infrastructure, eval tooling, model serving, prompt management, observability, and safety guardrails. The role involves owning the full lifecycle from problem framing to production deployment, ensuring the platform is reliable, performant, and easy to adopt. The Staff MLE will also shape technical standards, drive architectural decisions, and mentor engineers.

What you'd actually do

  1. Design and build scalable platform services — agent orchestration, RAG pipelines, eval frameworks, model serving — that internal teams use to ship AI-powered products.
  2. Lead technical strategy and architecture for the AI platform, including model lifecycle, observability, safety guardrails, and evaluation infrastructure.
  3. Collaborate cross-functionally with app teams, PMs, and Designers to understand their AI needs and deliver platform capabilities that unblock them.
  4. Build, harden, and operate shared infrastructure that powers intelligent agents across Gusto (e.g., retrieval, routing, prompt management, content selection).
  5. Stay current with AI/ML research; rapidly prototype and productionize new techniques that strengthen the platform.

Skills

Required

  • 12+ years building and deploying end-to-end AI/ML systems
  • experience designing platform-level infrastructure
  • Deep expertise in one or more areas: LLMs, NLP, retrieval/RAG, agent orchestration, deep learning, or reinforcement learning.
  • Hands-on experience building LLM-based applications and agentic workflows — including prompt engineering, retrieval design, evaluation, and production deployment.
  • Proficiency with modern ML frameworks (PyTorch, TensorFlow, Hugging Face)
  • Proficiency with cloud platforms (GCP, AWS, or Azure)
  • Strong Python skills
  • Sound software engineering fundamentals — testing, code review, CI/CD, reliability, and API design.
  • Demonstrated ability to lead cross-functionally
  • Influence technical direction
  • Communicate clearly with both engineers and non-technical stakeholders

Nice to have

  • Ph.D. or Master's in CS, ML, Statistics, Mathematics, or related field

What the JD emphasized

  • 12+ years building and deploying end-end AI/ML systems
  • experience designing platform-level infrastructure that other engineering teams build on
  • Proven track record shipping impactful AI/ML projects to production, ideally in a platform or infrastructure context.

Other signals

  • building foundational AI infrastructure
  • enabling product teams to build, test, and ship AI-powered experiences
  • owning the full lifecycle from problem framing to production deployment
  • mentoring engineers across the organization