Senior Technical Product Manager — Customer Workflow

FutureFit AI is on a mission to help more people get to better jobs faster and cheaper, focusing on those facing barriers to opportunity. They are seeking a Senior Technical Product Manager to lead the Customer Workflows domain, overseeing the entire experience for various stakeholders and driving product execution with a strong emphasis on AI integration.

Responsibilities:

• Own the Customer Workflows domain — the full experience of how employers, recruiters, business service teams, and staffing agents experience and interact with our technology
• Experience, performance, and activation across all recruiter-facing surfaces, including feature instrumentation and health metrics
• End-to-end workflows powering business service operations on the platform
• Tools, flows, and experiences that agents use to deliver value to employers and admins — increasingly augmented by agentic AI that handles routine steps and surfaces the next best action
• Surface and define agentic AI, LLM, search, and recommender applications — including candidate recommendations and automated business-service flows — translating them into clear requirements and the evaluation standards the data and engineering teams adopt
• Use AI agents and LLM tooling as your default work layer — generating working prototypes, drafting test plans, synthesizing customer interviews — and turn what you learn into reusable processes others adopt. Know when to manage a fleet of agents and when to stop and involve humans
• Run continuous, lightweight research (direct interviews, session reviews, portal data analysis), structured Jobs-to-Be-Done discovery sessions, and fast prototyping to get something testable in front of real users before committing engineering capacity
• Author and maintain quarterly roadmaps for the Customer Workflows domain, contribute to strategy discussions alongside the CPO, VP of Engineering, and VP of AI & ML, and connect employer/recruiter outcomes to ARR and mission goals — informed by competitor analysis, with a particular eye on agentic AI-native entrants
• Own trade-offs across performance, scalability, cost, and speed; translate ADRs and engineering context into precisely scoped tickets; write PRDs with clear acceptance criteria, explicit edge cases, defined data requirements, and a testable definition of done; partner with engineering and analytics leads on data warehouse initiatives such as large-scale integrations and ATS work
• Be the go-to product partner for Product, Engineering, Data, Customer Success, and GTM in your domain; proactively brief Sales and CS before major releases; mentor peers on technical scoping, evaluation frameworks, agentic AI workflow, and discovery craft; and create reusable templates, decision frameworks, and playbooks that raise the quality floor

Requirements:

• Demonstrated ownership of a product area at a platform level — you can articulate the what, why, and trade-offs of every major decision in your domain with authority
• A track record leading multi-quarter, cross-functional technical initiatives end-to-end
• You are AI-native, not AI-curious: you already use LLMs, agents, and AI-assisted tools as your primary work layer — not occasionally, not experimentally — and you know what different models are good at, where they fail, and how to orchestrate them to get real work done
• Strong technical depth: you can shape architecture discussions, evaluate agentic AI/LLM system quality, define evaluation frameworks, and scope non-functional requirements independently
• Data fluency: you define OKRs and success metrics with precision, maintain a living metrics view, and drive data-informed decisions — not just report on delivery velocity
• Proven cross-functional credibility: Sales, CS, and Engineering see you as a trusted partner, not a gatekeeper
• Experience with employer/recruiter, workforce, or B2B SaaS platforms
• Fluency in employer and workforce development policy: WIOA service delivery, Workforce Pell, and Eligible Training Provider List (ETPL) dynamics
• Familiarity with modern BI/analytics tooling (Looker, Snowflake, or equivalent)