Senior Product Manager

Role Description

Health Data Innovations is seeking a Senior Product Manager to lead product definition and execution for Automatix, HDI’s claims and administrative data automation platform. This individual will report to the Head of Product Development and partner closely with engineering, data operations, client success, and commercial leadership to translate the realities of payer and provider data workflows into a modern, scalable SaaS product.

This role sits at the intersection of healthcare administrative data, B2B SaaS product management, and AI-accelerated software development. The Senior Product Manager will own the Automatix roadmap, drive specification quality, and bring rigor to how AI tooling is used inside the product development lifecycle. A core expectation of this role is fluency with modern AI coding and analysis tools, including the ability to use models such as Claude to read legacy codebases, ingest screen captures, reconstruct undocumented behavior, and produce high-fidelity specification documents in collaboration with the development team. Equally important is a clear-eyed understanding of where AI adds leverage, where it does not, and what compensating controls are required when AI is embedded in product workflows that touch protected health information and claims data.

This is a high-impact role within a PE-backed platform with significant growth ambitions and a product portfolio that is central to HDI’s expansion across payer and provider clients.

Primary Responsibilities

• Own the end-to-end product lifecycle for Automatix, including roadmap definition, prioritization, specification, release planning, and post-launch measurement, in partnership with the Head of Product Development and engineering leadership.
• Lead the creation of detailed product specifications, technical requirements, and user stories that bridge legacy system behavior with target-state architecture, using AI tooling to accelerate discovery and reduce specification cycle time.
• Apply AI-assisted product workflows in a structured, auditable way, including using Claude and equivalent tools to read existing code, ingest screenshots and screen flows, reconcile undocumented business logic, and produce specification artifacts that engineering can build against with minimal rework.
• Establish and enforce the operating model for AI use across the product organization, including selection of tools, prompt and context standards, human review checkpoints, and compensating controls for areas where AI output is unsuitable or carries elevated risk.
• Run the product side of an Agile and DevOps software development practice for a SaaS platform, including backlog grooming, sprint planning, release management, definition of done, and continuous delivery discipline in coordination with engineering and quality.
• Translate the operational realities of healthcare payer and provider administrative IT into product requirements, with particular focus on claims data ingestion, normalization, validation, reconciliation, and downstream analytics consumption.
• Partner with data operations and client success to convert recurring client issues, integration patterns, and exception workflows into product features that reduce manual effort and improve data quality at scale.
• Define and track product KPIs that matter to a B2B healthcare SaaS business, including time-to-onboard, data quality metrics, throughput, exception rates, client retention drivers, and gross margin contribution from automation.
• Serve as the product voice in client-facing conversations with payer and provider stakeholders, including data executives, claims operations leaders, and analytics teams, capturing feedback in a structured way that informs roadmap decisions.
• Work with HDI’s information security and compliance functions to ensure that AI tooling, third-party services, and product features meet HIPAA, HITRUST, and client-specific data handling requirements, and that compensating controls are documented and tested.
• Collaborate with sales, marketing, and pricing on go-to-market readiness for new releases, including positioning, enablement materials, packaging, and pricing inputs grounded in the value the product delivers to payers and providers.
• Mentor product analysts and junior product managers as the team scales, and contribute to the broader product operating model at HDI as the company expands its platform footprint.

Qualifications

• Bachelor’s degree required; technical, analytics, or business graduate degree a plus.
• 8–12 years of progressive product management experience in B2B SaaS, with a meaningful portion of that experience focused on healthcare administrative IT, claims data, or healthcare analytics platforms serving payers, providers, or risk-bearing entities.
• Demonstrated ownership of one or more SaaS products through full lifecycle, including discovery, specification, build, launch, and iteration, with measurable outcomes tied to product performance and client value.
• Hands-on fluency with AI tooling for product work, including using large language models such as Claude to read legacy codebases, interpret screen captures, reconstruct undocumented behavior, and generate specification documents in collaboration with engineering.
• Clear-eyed understanding of the capabilities and limitations of current AI tooling in product management contexts, including failure modes, hallucination risk, data handling considerations, and the compensating controls required when AI is used in workflows that touch PHI or claims data.
• Strong working knowledge of Agile and DevOps practices for SaaS development, including backlog management, sprint cadence, release engineering, CI/CD, observability, and the partnership between product and engineering required to make those practices effective.
• Deep familiarity with healthcare administrative data, including claims, eligibility, provider, and remittance data, along with the standards, vendors, and workflows that govern how this data moves between payers, providers, and intermediaries.
• Particular interest and demonstrated experience working with claims data and analytics use cases, including data quality, normalization, reconciliation, exception handling, and downstream reporting and decision support.
• Experience writing high-quality product specifications, PRDs, and technical requirements that engineering teams can execute against with minimal ambiguity, including for products that integrate with or replace legacy systems.
• Comfort operating in a PE-backed environment with sponsor reporting expectations, value creation timelines, and a strong bias toward measurable progress.
• Excellent written and verbal communication skills, with the ability to work effectively across engineering, data operations, client success, commercial, and executive audiences.
• Hands-on, entrepreneurial approach with a bias toward action and comfort operating in ambiguity.