Senior Product Manager, AI
23 hours ago
Phoenix
Job DescriptionDescription: Job Title: Senior Product Manager Department: Product Reports To: Chief Product Officer Employment Type: Full-Time, Salary-Exempt, Remote Salary: $110,000-$140,000 About AccuSourceHR: AccuSourceHR is a full-service employment screening organization headquartered in Phoenix, Arizona. Since 1999, we have helped employers make faster, safer, and more confident workforce decisions through reliable screening technology, high-quality client care, and PBSA-accredited practices. We are investing in modern product experiences, integrations, automation, data-driven insights, and practical AI capabilities that help customers operate more efficiently and with greater confidence. Position Overview As a Senior Product Manager, you'll lead the end-to-end product life cycle, from ideation to launch and iteration. Collaborating with cross-functional teams, including engineering, UX/UI, operations, implementation, and marketing, you'll develop scalable, user-centric solutions that align with our mission to enhance workforce screening services. What you will own: Product Strategy and Roadmap • Own product strategy and roadmap for AI-enabled capabilities, workflow automation, data-driven insights, integrations, and platform improvements., • Translate customer problems, business goals, technical possibilities, and operational constraints into clear product priorities., • Define MVPs, phased releases, success metrics, rollout plans, and risk controls., • Build business cases tied to revenue, retention, efficiency, risk reduction, or competitive differentiation., • Partner with engineering to design, test, and launch AI-enabled features, copilots, assistants, agents, conversational experiences, and intelligent workflows., • Define user journeys, permissions, tool interactions, guardrails, fallback logic, escalation paths, confidence thresholds, and human review requirements., • Write clear requirements involving prompts, context engineering, structured outputs, retrieval, workflow orchestration, model limitations, evaluation criteria, and release readiness., • Design natural-language experiences that help users ask questions over complex data and receive structured, defensible answers such as summaries, tables, explanations, or recommended next steps., • Define release-readiness criteria for AI features, including hallucination handling, PII protection, audit trails, observability, rollback plans, and user transparency., • Develop deep understanding of customer workflows across screening, compliance operations, document management, monitoring, business-system integrations, and regulated operational environments., • Identify opportunities to connect fragmented workflows, data sources, partner systems, and customer operations into clearer product experiences., • Frame integration depth, data contracts, permissions, data quality, and build-versus-partner tradeoffs as product decisions., • Conduct customer discovery, stakeholder interviews, workflow analysis, competitive research, and market assessment., • Shadow or interview users who operate complex workflows so product decisions are grounded in real operator behavior, not assumptions., • Use customer feedback, support trends, usage data, sales input, implementation friction, and market signals to inform priorities., • Track foundation model releases, agent frameworks, AI evaluation methods, and relevant workflow automation trends., • Define personas, jobs-to-be-done, user journeys, problem statements, product hypotheses, and adoption risks., • Partner with engineering, security, compliance, legal, and operations to manage risks related to sensitive data, PII, bias, explainability, auditability, and human oversight., • Define when AI should recommend, summarize, classify, draft, automate, escalate, or stay out of the workflow., • Establish product-level AI governance practices, including evaluation criteria, monitoring, documentation, user transparency, audit trails, and release controls., • Define KPIs for adoption, workflow completion, time savings, quality, customer satisfaction, risk reduction, operational efficiency, and revenue impact., • Define AI-specific metrics such as task success rate, acceptance rate, escalation rate, hallucination rate, user trust, cost per successful outcome, and time saved., • A clear AI product roadmap is defined, prioritized, and aligned with company strategy., • High-value AI and automation opportunities are translated into MVPs, measurable outcomes, and risk-managed launch plans., • At least one AI-enabled capability, intelligent workflow, data-driven insight, or integration-driven experience is launched, piloted, or meaningfully advanced toward production., • Customer evidence from interviews, usage data, support trends, or adoption metrics shows that shipped capabilities are solving real workflow problems., • A practical evaluation approach is established so AI quality, safety, and regression risk are visible to the team., • 7+ years of product management experience in B2B SaaS, workforce technology, compliance software, transportation technology, enterprise workflow software, data products, automation products, or a related domain., • 1 to 2+ years shipping AI/ML, generative AI, intelligent automation, conversational analytics, agentic workflows, or data-driven workflow products to real users., • Ownership of at least one AI-powered or agent-based capability, such as a co-pilot, assistant, intelligent automation, multi-step workflow, conversational interface, recommendation system, or AI-assisted workflow., • Strong technical fluency in LLMs, prompt design, context engineering, retrieval-augmented generation, structured outputs, agent frameworks, evaluation methods, and cost, latency, quality, and safety tradeoffs., • Experience defining product strategy, requirements, user stories, acceptance criteria, success metrics, rollout plans, and post-launch iterations., • Strong product judgment, including the ability to decide when AI is appropriate and when deterministic workflow automation is better., • Experience with sensitive data, regulated workflows, compliance-heavy products, high-trust customer environments, or enterprise systems., • Strong analytical, written, and verbal communication skills., • Experience with employment screening, drug screening, employment verification, credentialing, license or certification tracking, continuous monitoring, audit readiness, regulated operations, document management, healthcare, transportation, employee life cycle, or compliance-heavy workflows., • Experience launching AI-powered features, agents, copilots, workflow automation, recommendation systems, or data-driven decision support into production., • Experience designing conversational or natural-language interfaces over complex enterprise data., • Experience designing or operating LLM or agent evaluation systems, including golden sets, regression evals, LLM-as-judge, online experimentation, or human review workflows., • Familiarity with Claude, ChatGPT, Amazon Bedrock, Azure OpenAI, GitHub Copilot, Cursor, LangChain, LlamaIndex, vector databases, MCP-based connectors, LangGraph, AutoGen, CrewAI, Bedrock Agents, or AI evaluation tools., • Working understanding of embeddings, retrieval architectures, data quality issues, permissions, enterprise identity, and enterprise data access patterns., • Strategic but hands-on: You can shape a roadmap and still get into workflows, edge cases, acceptance criteria, launch readiness, and post-launch learning., • AI-aware, not AI-hyped: You are excited about AI but realistic about quality, risk, cost, privacy, reliability, model limitations, and customer trust., • Technically fluent: You can discuss APIs, data flows, integrations, permissions, model behavior, evaluation, observability, and tradeoffs with engineering., • Production-minded: You understand that AI quality must be tested, monitored, supported, and improved after launch., • Domain-curious: You are willing to learn the details of regulated workflows, operational edge cases, and customer processes., • Customer-obsessed: You care about whether the product solves the customer’s problem, not just whether the feature shipped., • Help shape practical AI-enabled products with real customer value., • Work on AI, automation, integrations, and data-driven insights in complex business workflows., • Partner directly with executive product leadership in a visible, high-impact role., • Medical (with company contribution), • Dental (with company contribution), • Vision, • Employer paid Life Insurance and Long-Term Disability, • Short-Term Disability, • 401(k) (with company match), • Paid holidays, • Paid time off (PTO), • Sick Time, • Must have a dedicated and ergonomic workspace at home conducive to focused work., • Access to a stable and reliable high-speed internet connection., • Adequate lighting and minimal background noise to support professional video calls and meetings., • Ability to lift and carry up to 5 pounds occasionally, for tasks such as setting up a workstation or equipment.