Lead AI Engineer

Lead AI Engineer Description About When When is a US-based, venture-backed company that has built a novel AI-driven health insurance marketplace and post-employment platform. Our product will transform how companies offboard employees and how people manage their transition between jobs. The Opportunity We’re looking for a Lead AI Engineer to own and scale the intelligent systems at the core of When’s platform. This is not a research role—it’s a builder role with a business lens. You’ll design and deliver the AI infrastructure that powers our conversational assistants, intelligent recommendations, and guided decision-making workflows, all while ensuring we can measure, understand, and improve how those systems serve real users. You’ll work directly with the CTO to translate our AI vision into a robust, production-grade platform. That means thinking beyond “does the feature work?” to “how do we track whether it’s working for users, how do we scale it, and how does it connect to business outcomes?” You’ll own the full lifecycle: architecture, data pipelines, analytics instrumentation, and the operational rigor that separates a prototype from a platform. When is an AI-first company. We’re rapidly expanding our AI capabilities across every surface of the product—from user-facing chat agents to internal tools that help our member services team operate more effectively. You’ll be the senior technical voice shaping how we build, measure, and grow all of it. What You’ll Do AI Platform Architecture & Infrastructure Own the end-to-end architecture of When’s AI systems—from LLM orchestration and agent frameworks to data pipelines, model serving, and observability Design scalable, maintainable infrastructure that supports rapid experimentation without sacrificing reliability—thinking through failure modes, fallback strategies, and system-wide impact before building Build and maintain the data layer that captures how AI features are used: structured logging, event pipelines, and integration with analytics and reporting tools Future-proof our AI stack so new models, capabilities, and partner integrations can be adopted without re-architecture AI-Powered Product Experiences Lead the design and development of AI-driven features embedded in the product—conversational assistants that guide users through COBRA elections, ACA marketplace enrollment, 401k rollover, and benefits decisions Build systems that serve both our end users and our member services team—ensuring internal teams can track how users interact with AI tools, identify where users struggle, and intervene when needed Design AI interaction patterns that build trust: streaming responses, confidence indicators, graceful degradation, and human-in-the-loop escalation paths Collaborate with the UX team to translate AI capabilities into intuitive interfaces that drive measurable user outcomes Data, Analytics & Business Intelligence Instrument AI features with structured tracking that answers business questions: How are users engaging? Where do they drop off? What drives conversion? Where does the AI add value vs. create friction? Build reporting infrastructure that gives Product, Member Services, and leadership visibility into AI performance—usage patterns, sentiment, resolution rates, and ROI Design and run experiments (A/B tests, prompt variations, workflow comparisons) with proper measurement frameworks to continuously optimize AI-driven experiences Partner with Product and Data teams to define the metrics that matter and build the feedback loops that make them actionable Strategic Partnership & Technical Leadership Work directly with the CTO to develop and execute When’s AI strategy—evaluating new models, tools, and approaches with a critical eye on business impact and scalability Bring a systems mindset to every decision: how does this feature affect our data model? What downstream dependencies does it create? How will we maintain it at 10x scale? Serve as the AI technical authority across the engineering org—providing guidance on best practices, code reviews, and architectural decisions Contribute to hiring and team development as When’s AI capabilities grow Who You Are 5+ years of experience in software engineering with at least 2–3 years focused on AI/ML systems, LLM integration, or intelligent product features in production environments Proven track record building AI systems at scale—not just prototyping, but shipping, instrumenting, and maintaining production AI infrastructure Strong systems thinking: you instinctively consider scalability, reliability, observability, and downstream effects when making technical decisions Deep experience with LLM orchestration frameworks (LangChain, LangGraph, or similar), prompt engineering, and agent architectures Hands-on experience building data pipelines and analytics instrumentation—you know how to make AI systems observable and measurable Experience with cloud infrastructure (GCP preferred; AWS or Azure acceptable) including model serving, data storage, and event pipelines Fluent in AI-assisted development workflows—you actively use tools like Claude Code, Cursor, GitHub Copilot, or similar in your daily work and can evaluate their output critically Strong business acumen: you think about AI features in terms of user outcomes, conversion, support deflection, and ROI—not just technical novelty Excellent communication skills—you can explain complex AI systems to product managers, member services teams, and executives with equal clarity Comfortable with ambiguity and ownership; you thrive in early-stage environments where you’re building the playbook, not following one Nice to Have Experience in health insurance, benefits administration, COBRA, Medicare, or regulated industries where AI accuracy directly impacts compliance and user outcomes Background building conversational AI products (chat agents, recommendation engines, intelligent forms) that serve both end users and internal operations teams Experience with evaluation frameworks for LLMs—designing evals, measuring quality, and building feedback loops that improve model performance over time Familiarity with GCP services (BigQuery, Cloud Functions, Pub/Sub, Vertex AI) in the context of AI infrastructure and analytics Experience at an early-stage startup (<50 employees) where you owned a technical domain end-to-end Python and TypeScript proficiency; experience with GraphQL APIs Preferred locations: Chicago, IL. US-based, remote. Compensation & Perks Competitive base salary + equity 100% company-paid health insurance High-visibility role reporting directly to the CTO with significant influence over product and AI strategy Opportunity to define When’s AI platform architecture and analytics foundation from the ground up Collaborative, mission-driven team that values craftsmanship and impact The salary range for this position is: $160,000 – $180,000. When considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. Actual compensation will vary based on these considerations. About the Company When is a US-based, venture-backed company that has built a novel AI-driven health insurance marketplace and post-employment platform. Our product will transform how companies offboard employees and how people manage their transition between jobs.