AI Product Manager

Hydrogen Group; San Diego (CA); Hybrid; USD 154,000 - 161,000; Part time

Job summary

Hydrogen Group is seeking an AI Product Manager in San Diego for a 6-month hybrid role. You will lead the definition, delivery, and scaling of AI-enabled products across enterprise workflows, partnering with data science, engineering, and platform teams to deliver solutions from concept through production.

The role requires strong product management, ROI-driven thinking, and experience with AI governance and regulatory considerations in complex environments.

Qualifications

• Bachelor's degree in CS/IT/Engineering, or related field.
• 5+ years of product management across enterprise, data, or technology products.
• Hands-on experience delivering AI-enabled analytics or automation solutions.
• Experience collaborating with engineering, data science, and business teams.
• Experience in regulated environments; life sciences preferred.

Responsibilities

• Define product strategy, roadmap, and success metrics for AI initiatives.
• Identify and prioritize high-value AI opportunities aligned with business goals.
• Translate business needs into actionable requirements and user stories.
• Lead backlogs, sprint planning, and stakeholder reviews for AI products.
• Ensure AI capabilities are scalable, production-ready, and compliant with governance.

Skills

Product management

Stakeholder management

AI knowledge

Roadmapping

MVP development

Cross-functional collaboration

Critical thinking

Communication

Education

Bachelor's degree (CS/IT/Eng/Business)

Tools

Microsoft platforms

Workflow automation tools

Job description

AI PRODUCT MANAGER

LOCATION: SAN DIEGO, CA (HYBRID)

DURATION: 6-MONTH CONTRACT

PAY: 112-117 USD

Job Responsibilities

In this role, you will lead the definition, delivery, and scaling of AI-enabled products across enterprise and scientific workflows. Key responsibilities include:

• Developing and managing the product vision, roadmap, and success metrics for assigned AI use cases.
• Identifying and prioritizing high-value AI opportunities aligned with business objectives.
• Translating complex and ambiguous business problems into clear product requirements and user stories.
• Partnering with data science, engineering, and platform teams to deliver AI-powered solutions from concept through production.
• Managing product backlogs, sprint planning, prioritization, and stakeholder reviews.
• Ensuring AI products are production-ready, scalable, and operationally supported.
• Rapidly testing assumptions, refining scope, and developing MVPs that balance business impact, technical feasibility, and risk.
• Collaborating with subject matter experts across R&D, Clinical, Regulatory, Quality, Medical Affairs, Manufacturing, Finance, and Commercial.
• Acting as the primary connection between business stakeholders and technical teams.
• Ensuring AI solutions meet applicable governance, risk, compliance, and data requirements.
• Supporting adoption, enablement, change management, and go-to-market activities.

Essential Duties and Job Functions

• Own product strategy and roadmap for assigned AI initiatives.
• Define clear product requirements, user stories, acceptance criteria, and prioritized backlogs.
• Conduct discovery activities to identify and evaluate opportunities for applied AI.
• Translate business needs into actionable requirements for engineering and data science teams.
• Lead backlog prioritization, sprint planning, product reviews, and delivery discussions.
• Coordinate with data science, engineering, platform, and business teams throughout product development.
• Ensure AI capabilities are scalable, production-ready, and appropriately supported after launch.
• Define human-in-the-loop workflows, guardrails, controls, and success criteria for AI solutions.
• Ensure appropriate documentation, auditability, and controls are incorporated into AI products.
• Partner with Legal, Compliance, Quality, and IT to address regulatory and data governance requirements.
• Support GxP and validation considerations where applicable.
• Define and monitor product success metrics, including adoption, business value, quality, and risk indicators.
• Gather user feedback and performance data to continuously improve AI products.
• Manage stakeholder expectations, priorities, tradeoffs, and delivery timelines.
• Maintain alignment between business, technical, and compliance stakeholders.
• Support product enablement, change management, and adoption initiatives.

Knowledge & Skills

• Strong product management, communication, documentation, and stakeholder management skills.
• Strong understanding of artificial intelligence, generative AI, analytics, and automation.
• Ability to translate complex business problems into structured product requirements.
• Experience working closely with engineering, data science, and business teams.
• Strong understanding of product discovery, roadmapping, prioritization, MVP development, and iterative delivery.
• Ability to evaluate AI opportunities based on business value, technical feasibility, and risk.
• Understanding of AI governance, risk management, compliance, and data governance.
• Familiarity with human-in-the-loop workflows, AI guardrails, and responsible AI practices.
• Strong analytical, organizational, problem-solving, and critical-thinking skills.
• Excellent written and verbal communication skills.
• Ability to manage competing priorities in a complex, matrixed environment.
• Ability to collaborate effectively with technical and non-technical stakeholders.
• Ability to operate independently and onboard rapidly within a lean team.
• Familiarity with enterprise technology, Microsoft platforms, data platforms, and workflow automation tools.

Education & Experience

• Bachelor's degree in Computer Science, Information Technology, Business, Engineering, Life Sciences, or a related field.
• 5+ years of product management experience across enterprise, data, digital, or technology products.
• Hands-on experience delivering AI-enabled, analytics, or automation solutions.
• Experience working cross-functionally with engineering, data science, and business teams.
• Experience working in complex, matrixed, and regulated environments.
• Experience in life sciences, pharmaceuticals, biotech, or medical devices preferred.
• Familiarity with GxP, clinical, quality, regulatory, or validation workflows preferred.
• Experience with generative AI, LLMs, intelligent automation, or advanced analytics preferred.
• Experience with enterprise platforms, data platforms, and workflow tools preferred.
• Experience managing portfolio-level or multi-use-case AI initiatives is a plus.