Futurefit AI Senior AI Engineer at FutureFit AI to build LLM-based AI products that guide job seekers to better jobs. Own product development, evidence-based coaching, and AI evaluation quality.
Responsibilities
We're seeking a Senior AI Engineer to join our team.
The centerpiece of this role is our coaching products. We want to tell a job seeker not just what jobs exist, but which specific next step is most likely to move their life forward, grounded in evidence we can defend: transitions we have observed in labor market data, and interventions we have measured as causally lifting wages and lifetime earnings. You will own both halves: establishing what the evidence supports, and the engineering that turns it into a product a person can use.
This is a hands-on, high-ownership role on a small team. You will partner closely with Engineering, Product, and the VP of Data & AI, and you will have wide latitude to decide how these systems get built.
LLM product development: Design, build, and ship LLM-based product experiences end to end: conversational coaching, agentic workflows that complete multi-step tasks for a user, and the tool use and orchestration layers underneath them.
Coaching and pathways, grounded in evidence: Build the products that guide a job seeker to their next best step, and do the analysis that earns those recommendations: observed career transitions, causal impact on wages and lifetime earnings, and an honest assessment of what our data can and cannot claim.
Evaluation and quality: Own how we know our AI is any good. Build the eval harnesses, offline and online quality measurement, regression tracking, and human-in-the-loop review that let us ship fast without shipping something harmful or wrong.
Applied ML beyond LLMs: Build predictive, classification, and ranking models when that is the right tool for the product problem, and have the judgment to know when it is.
Data engineering for AI: Prepare, label, govern, and maintain the pipelines and knowledge sources our AI systems depend on, so retrieval and reasoning are grounded in data we trust.
Integration engineering: Connect our AI systems safely to internal tools, databases, SaaS products, case management systems, and enterprise workflows, with the auth, guardrails, and failure handling our customers' environments demand.
Where This Role Can Go
This role carries real influence over how we build. You will help shape the patterns our AI work runs on: how we prompt, how we evaluate, and how we decide what an agent is allowed to do on someone's behalf. You will do it while building brand new products, with room to show technical leadership across the team.
From there, the path is yours to steer: deeper technical leadership over our AI platform, or broader ownership of the coaching and pathways products themselves. What matters most to us is a willingness to learn, adapt as the product changes, and stay open to unfamiliar work, and we'll build the path with you.
Qualification
Experience with AWS and SageMakerExperience with jobs-and-skillsExperience with recommender systemsExperience with labor economicsPublicationsOur Tech Stack for Data & AI
Preferred
Experience with AWS and SageMaker, or building and deploying AI systems on AWS more broadly
Experience with jobs-and-skills, HR, or labor market data, or with skills/occupation frameworks such as O*NET or ESCO
Experience integrating with case management systems, government systems, or other public-sector data environments
Experience with recommender systems, ranking, or search at scale
Experience with retrieval-augmented generation at production scale, including retrieval quality evaluation
Experience with labor economics, program evaluation, or measuring the impact of workforce interventions
Publications, talks, blog posts, or open source work showing your depth in AI or ML engineering