Sr. Director of Engineering

Senior Director, Product Engineering

Build AI that clinicians and educators can trust. A builder-leader role for someone who can move from architecture to prototype to production in a high-trust, mission-driven domain.

Reports to VP of Product, Design, & Engineering - Location Remote / Hybrid; occasional in-person - Travel Minimal - Compensation $250K-$280K base + bonus

Every year, clinicians and educators rely on WPS to support children with autism, learning differences, and developmental needs. We are building the next generation of tools for high-stakes assessment work - tools that are rigorous, humane, reliable, and ready for responsible AI.

We are hiring a Senior Director of Product Engineering to help lead that transformation. You will set product engineering architecture, lead applied AI development, build the technical foundation for safe AI features, and ship customer-facing capabilities that make practitioners faster, more precise, and more confident.

Real ownership Visible authority over architecture, technical standards, and applied AI direction. - Meaningful impact Build tools that support clinicians, educators, children, families, and care teams. - Careful AI Join a culture that values judgment, evidence, privacy, safety, and trust over AI hype.

Your year-one mission: three applied AI bets

• Semantic search Enable practitioners to search WPS clinical and educational content with speed, precision, and trust.
• AI-assisted narratives Help clinicians generate accurate, defensible written reports from structured assessment data.
• Evaluation framework Build LLM feature evaluation practices that protect accuracy, safety, privacy, and regulatory standing.

What you'll own

• Own product engineering architecture: modernize what slows the business down and ship what moves customers forward.
• Build the WPS AI foundation: permissions-aware content retrieval, evaluation harnesses, telemetry, audit logs, and feedback loops.
• Design, prototype, and ship AI/LLM-powered capabilities, including RAG pipelines, agent workflows, and evaluation frameworks.
• Set technical strategy alongside Product, Design, Clinical, Research, and Sales stakeholders.
• Establish standards for cloud architecture, CI/CD, observability, model governance, privacy, safety, and accessibility.
• Define metrics that matter: system reliability, delivery velocity, model quality, adoption, and practitioner trust.
• Mentor engineers and build a culture where technical excellence and shipping velocity are both expected.

What we're looking for

• Must-haves
• 10+ years in software engineering, including meaningful architecture and product delivery ownership.
• 3+ years leading engineers, with evidence that you can still go deep technically.
• Production software experience in a high-accuracy, high-trust, or regulated environment.
• Hands-on experience shipping or evaluating LLM-powered features, RAG systems, agent workflows, or AI-enabled product surfaces.
• Experience modernizing an existing product or platform while continuing to ship customer value.
• Strong cross-functional judgment with Product, Design, domain experts, and non-technical executives.
• Strong signals
• Clinical, education, assessments, healthcare, publishing, or expert-content domain experience.
• Built or led an applied AI engineering team.
• Experience with model governance, MLOps, evals, safety guardrails, and auditability.
• Cloud-native systems architecture across AWS, GCP, or Azure; distributed systems, APIs, and data platforms.
• A track record of moving quickly and responsibly in ambiguous environments.
• Curiosity about emerging technologies without being locked into a single tool, stack, or preference.

You may thrive here if

• You are energized by owning the path from architecture to prototype to production.
• Building high-performing teams while staying close to the work.
• Using AI thoughtfully to increase leverage, not replace judgment.
• Partnering with Product to translate customer problems into technical solutions.

This role is not for you if

• You prefer strategy decks to shipped systems, evals, user feedback, and production tradeoffs.
• You want to manage managers from a distance and avoid hands-on technical work.
• You are casual about clinical accuracy, privacy, accessibility, or explainability.
• You need a fully specified roadmap before making progress.

What success looks like early

• Days 1-30 - Learn the products, customers, and technical landscape. Build stakeholder trust. Identify a quick-win AI or engineering improvement. Deliver a clear current-state POV.
• Days 31-60 - Prototype or ship the quick win. Align on architectural priorities and the 6-month roadmap. Establish the foundation for LLM evaluation practices.
• Days 61-180 - Drive execution against aligned priorities. Move one AI bet toward production or pilot. Present a forward-looking roadmap linked to business outcomes.

At 12 months, success means... WPS has materially advanced all three AI bets; at least one capability is in production, one is in pilot with real users, and one has validated architecture, evaluation practices, and roadmap. Engineering velocity, reliability, and trust metrics have improved, and executive leadership recognizes this leader as the technical owner of WPS's AI transformation.

How to apply Send your resume and a Loom walkthrough of an AI feature, product, or project you built in the last year. We care more about builder judgment than polish. Show us what you built, what tradeoffs you made, how you evaluated quality, and what you learned.

The bottom line This is a high-impact role for a leader who wants to build responsible AI in a domain where quality, evidence, and human trust matter. If you are excited to modernize product engineering, lead applied AI delivery, and build systems that help practitioners do meaningful work with more clarity and less burden, we would like to meet you.

WPS - unlocking potential