Sr. Technical Product Owner AIML & Agentic Systems

Speridian Technologies is recruiting for a Senior Technical Product Owner - AI/ML for our State of California Client the Department of Healthcare Services Behavioral Health. This person will be part of a long-term fully budgeted state-of-the-art extremely vast technical modernization project working with a variety of cross-functional teams and stakeholders.

This is a remote role; however there will be meetings in the Sacramento area several times a year. Candidates are expected to work business hours Monday-Friday Pacific Time Zone.

Join DHCSs Behavioral Health Transformation: Where Purpose Meets Innovation
Location:Remote
Department:Department of Healthcare Services (DHCS) Behavioral Health Transformation (BHT)
Commitment:Full-Time Consultant (W2 employee of Speridian or 1099/IC for Speridian)

Why DHCS
At DHCS we are leading a transformative journey in Behavioral Health reshaping systems and services toensure better outcomesfor communities across California. Our Behavioral Health transformation initiative is more than a projectits a movement to make California a leader in accessible high-quality health services. Were setting the stage for a new era of government services built on agile methodologies cutting-edge technology continuous improvement and a relentless commitment to serving the public good.
At DHCS were looking for innovators who are passionate about purposeful work and excited by the opportunity to drive lasting change through innovative solutions.

Our core values are what make us successful and define the impact we have on the DHCS program and Californias citizens.

• Partnership: Respect Other Practice Empathy Earn Trust
• Ownership:Take Accountability Show Reliability Act with Integrity
• Grit:Bring Passion Exhibit Perseverance Demonstrate Resilience
• Value:Drive Outcomes Maximize Impact Keep Improving

Responsibilities

Lead with full accountability for the teams backlog in this area. This includes not only maintaining the backlog but owning its strategic direction and ensuring it reflects the evolving priorities of the Behavioral Health Transformation (BHT) initiative.

• Backlog Ownership & Prioritization

  • Own and manage the AI/ML product backlog including GenAI and Agentic AI use cases.

  • Translate business problems into AI opportunities and actionable user stories with clear acceptance criteria tied to measurable outcome.

  • Prioritize backlog items to align with BHT objectives compliance deadlines and user value while balancing short-term delivery needs with long-term platform scalability.

  • Ensure features align with business value model performance ethical risk and technical feasibility.

  • Facilitate backlog grooming refinement and planning sessions with cross-functional teams.

  • Ensure clarity feasibility and alignment across engineering HCD and policy stakeholders.

  • Act as the primary link between legal policy technical and user domains. Translate complex requirements into actionable epics features and user stories with clear acceptance criteria and measurable outcomes.

  • Proactively manage delivery risks identify cross-team dependencies and ensure the team is consistently focused on the highest-value work.

  • Serve as the authoritative voice on what gets built when and why. Own the product narrative from Product Management and delivery outcomes from discovery through deployment.

• Strategic Alignment & Delivery

  • Active Partnership with Product Manager to define and evolve the product roadmap for AI/ML capabilities retrieval augmentation autonomous agents generative and predictive models.

  • Collaborate with Product Managers to define and track objectives and key results (OKRs)

  • Align delivery with capability OKRs AI governance frameworks and responsible AI principles.

  • Partner with AI/ML engineering leads to ensure model lifecycle management from experimentation to deployment and monitoring.

  • Ensure delivery timelines align with BHT milestones and federal interoperability requirements.

  • Partner with Agile Delivery Managers to manage sprint cadence burn rate and resource allocation.

• AI/ML Platform & Solution Development

  • Guide the development of AI-powered features such as:

    • Agentic workflows for autonomous task execution

    • Natural language interfaces and copilots

    • Predictive analytics and decision support tools

    • Retrieval-augmented & Generative workflows

    • AI-enhanced data pipelines and feedback loops

  • Ensure solutions are scalable explainable and aligned with DHCS/BHT architecture and data privacy standards.

  • Collaborate with MDE teams to support continuous integration and delivery of AI models.

• Stakeholder & Policy Integration

  • Review discovery workshops designs and interviews from the Operational Capability area to identify high-impact AI use cases align with Epics stories and acceptance criteria.

  • Serve as the bridge between business stakeholders and technical teams.

  • Ensure AI solutions are human-centered accessible and aligned with user intent and workflows.

  • Champion the voice of the user in AI product decisions especially in high-stakes or regulated workflows.

  • Facilitate feedback loops from frontline users and route feature requests appropriately.

• Metrics & Continuous Improvement

  • Define and track success metrics.

  • Use analytics to drive backlog prioritization and product enhancements.

  • Lead discovery and prototyping efforts to validate new features.

  • Promote a culture of continuous learning iteration and user-centered design.

• Collaboration & Leadership

  • Lead agile ceremonies and foster cross-functional collaboration across engineering HCD policy and delivery teams.

  • Champion the voice of care workers program and county users in product decisions.

  • Act as a thought leader in AI/ML product strategy agentic system design and responsible innovation in collaboration with engineering partners

  • Evangelize AI capabilities across the organization and support change management efforts.

  • Stay current on emerging AI trends tools and regulatory developments.

Qualifications

DHCS is recruiting for skills that reflect the broader leadership systems thinking and cross-functional coordination required for this role especially given the legal sensitivity and statewide scope of an AIL/ML platform or application.

• Experience

  • 7 years in product ownership or technical product management with 3 years focused on AI/ML or data science products.

  • Proven experience delivering AI/ML solutions in production including LLMs GenAI or autonomous agents.

  • Experience working with cross-functional teams including data scientists ML engineers and UX researchers.

  • Familiarity with MLOps model governance and AI observability tools.

  • Experience in regulated industries (e.g. healthcare finance public sector) is a plus.

• Skills

  • Ability to assess and manage product risk across legal technical and operational domains

  • Proficient in managing Agile workflows using Atlassian tools such as Jira Confluence and Bitbucket for backlog management documentation and collaboration.

  • Experience with AWS AI/ML services including SageMaker Bedrock Comprehend Rekognition and Lex as well as integration with AWS data pipelines and security frameworks.

  • Skill in navigating ambiguity and making decisions with incomplete information

  • Ability to synthesize user research policy analysis and technical constraints into cohesive product direction

  • Familiarity with data governance principles and consent lifecycle management

  • Experience coordinating go-to-market strategies for public-facing or field-deployed applications

Additional Preferred Skills

• Ability to assess and manage product risk across legal technical and operational domains

• Skill in navigating ambiguity and making decisions with incomplete information

• Ability to synthesize user research policy analysis and technical constraints into cohesive product direction

• Comfort working with executive stakeholders and presenting complex topics in plain language

• Experience with prompt engineering or agent orchestration frameworks.

• Knowledge of ethical AI principles bias mitigation and explainability techniques.

• Certification in Agile Product Ownership.

• Background in data science computer science or a related technical field.