Lead AI Engineer

It's fun to work in a company where people truly believe in what they're doing!

We're committed to bringing passion and customer focus to the business.

Trio WFS builds Digital Workers, autonomous AI systems that execute real operational workflows in healthcare workforce management, already running in production and delivering measurable results for our clients.

The Lead AI Engineer is the senior technical authority for this work, responsible for driving the architecture, technical direction, and engineering standards that support Trio's AI-powered products, Digital Workers, and intelligent automation capabilities.

This role leads the design and evolution of complex AI systems spanning agentic workflows, retrieval-augmented generation (RAG) architectures, orchestration frameworks, evaluation platforms, observability capabilities, and product AI infrastructure. The Lead AI Engineer operates as the technical leader for the AI Engineering team, influencing architecture decisions across Trio's products while partnering closely with Product, Engineering, Data, Platform, and executive stakeholders.

This role is being developed with a clear path toward team leadership. The ideal candidate combines deep technical expertise with a genuine desire to grow into people management, and will be coached and mentored to eventually lead the AI Engineering team.

This is a hands-on technical leadership role on a small, high-leverage team of one Senior AI Engineer and one AI Engineer, with direct exposure to Engineering, Product, and executive leadership.

What You'll Work OnThe Digital Worker framework, a pattern where policies (the questions a client needs answered) combine with features (the data available to answer them) to produce grounded, auditable decisions. Extending this framework to new workflows is the core of the job.

Evaluation infrastructure, the harness that lets us quantitatively measure whether a change to a prompt, retrieval strategy, or model actually improved anything. This gates what ships.

Platform orchestration, an event-driven orchestrator with autoscaling, input-level quarantine, and per-worker circuit breaking.

Centralized inference, an LLM gateway that routes, logs, and controls cost and latency across every AI-powered capability in the product.

Retrieval and knowledge systems, ingestion, embedding, indexing, and grounding strategies that keep answers accurate and traceable.

Principal Responsibilities Architecture & Technical Direction Own the architecture of the Digital Worker platform and the AI capabilities embedded in Trio's products

Establish design principles, engineering patterns, and architectural standards for AI systems

Lead technical design reviews and make the tradeoff calls on quality, latency, cost, and operational complexity

Evaluate emerging AI technologies and determine what is worth adoptingAI Systems Engineering Design and build production systems using LLMs, retrieval architectures, agentic workflows, and tool use Build reusable frameworks for agent orchestration, tool integration, workflow execution, and memory

Solve the hardest technical problems on the team, hands-on Evaluation & Quality Own the standards for how we measure AI quality: accuracy, groundedness, safety, latency, and business impact

Build and extend evaluation frameworks that catch regressions and hallucinations before clients do Drive measurable improvement in system quality through experimentation and production learning

Observability & Operational Excellence Define monitoring, tracing, and logging standards for AI systems in production

Establish reliability and performance objectives; serve as senior escalation for critical AI production issues

Improve production readiness and AI lifecycle management as the platform scales

Technical Leadership & Partnership Mentor the AI Engineering team and grow their architectural judgment and engineering depth

Lead code and design reviews; set and enforce engineering standards

Partner with Product, Platform, Data, Security, and executive stakeholders

Translate business objectives into technical strategy, and technical tradeoffs into business terms

Growth Path We are hiring a technical leader first. As the AI Engineering team grows, this role is expected to take on formal leadership of it. We will discuss what that path looks like openly during the interview process, including timeline expectations and what the transition into people management actually involves.

Education Required:

Bachelor's degree in Computer…