• Work with senior Product Management team members to set product goals and prioritize feature development. • Serve as the lead system prompt engineer, creating and maintaining the detailed instructions passed to the LLMs that power Theia Analyst. • Develop and implement processes to evaluate and monitor the performance of the tool. • Provide training and support to internal teams working with Theia Analyst, and consult on all client implementations. • Work directly with clients to conceptualize, test, and roll out new product features. • Collaborate with Sales and Marketing teams to articulate differentiated messaging for our AI solutions and design and run product demos. • Stay up to date on frontier LLM capabilities and suggest and implement product enhancements as the technology evolves.

• Join the team owning CreatorIQ’s reporting product suite, including Campaign Reporting, Enterprise Dashboard, and Competitive Reporting, to help customers analyze and optimize their influencer marketing programs. • Support end-to-end product lifecycle for the Campaign and Program Reporting portfolio, from discovery through delivery and iteration. • Contribute to a customer-centric, data-informed product roadmap aligned with company objectives and measurable business outcomes. • Collaborate with data-focused stakeholders to integrate complex, large-scale data sources across the ecosystem while ensuring accuracy, consistency, and scalability of reporting capabilities across the CreatorIQ ecosystem. • Define and track key performance indicators to measure the success of reporting tools. • Work closely with engineering and design teams to ensure high-quality product delivery. • Conduct market research and competitive analysis to inform product strategy and roadmap. • Present product updates and insights to internal stakeholders and clients, ensuring alignment and clear communication of product vision and goals.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description The Technical Product Manager role for Clinical solutions merges product management, healthcare expertise, and technical knowledge to develop and manage software and technology solutions for Alignment Health. - Drive the functional and technical roadmap for Clinical Solutions, including Utilization, Care Management platforms, Clinical decision support systems, quality measures, and interoperability solutions leveraging Alignment’s proprietary AVA and Vendor platforms. - Ensure compliance with CMS, NCQA, HIPAA, and other regulatory requirements impacting clinical data and processes. - Anticipate regulatory and operational changes (e.g., CMS rule updates, encounter data submission requirements) and integrate them into the roadmap. - Lead the design, testing, and implementation of new features for Clinical solutions platforms. - Define and drive integration with Electronic Health Records (EHRs), Health Information Exchanges (HIEs), and other clinical data platforms via APIs, HL7, FHIR, and batch interfaces. - Partner with data engineering teams to design solutions that support risk adjustment, HEDIS/Stars quality reporting, care gap closure, and population health analytics. - Define and prioritize features for provider-facing tools such as prior authorization, utilization management, case management, and clinical documentation improvements. - Collaborate with clinicians, business stakeholders, and technology teams to translate clinical workflows and requirements into scalable technical solutions. Qualifications - 5+ years of Product Management experience in healthcare technology, with a focus on clinical solutions. - Advanced degree or clinical background (RN, PharmD, MPH, etc.) strongly preferred. - Proven hands-on expertise with healthcare interoperability standards (FHIR, HL7, X12, CCD, CDA). - Microsoft SQL (querying, optimization, reconciliation, audits). - ETL Tools such as Microsoft SSIS and Azure Data Factory. - Cloud Platforms (Azure/AWS). - Experience integrating vendor solutions. - Strong knowledge of clinical workflows, care management, utilization management, and quality reporting. - Strong analytical, problem-solving, and communication skills with the ability to translate technical details into business outcomes. Requirements - Bachelor’s degree in Healthcare Information Systems, Computer Science or related field; advanced degree or clinical background (RN, PharmD, MPH, etc.) strongly preferred. - MBA or advanced degree preferred. - Deep understanding of Provider Credentialing, Contracting and Reimbursement Strategies in a Medicare environment. - Experience with Medicare and Medicaid programs, including Stars, HEDIS, and risk adjustment. - Knowledge of clinical natural language processing (NLP) or AI-driven care management tools. - Proficiency in relevant technical tools, such as SQL, Azure Data Factory, Jira, and Confluence. - Experience in defining product strategies, managing product backlogs, and working within agile development methodologies. - Familiarity with payer platforms (Facets, QNXT, HealthRules) and provider EMRs (Epic, Athena, Cerner, Allscripts). - Vendor management and SLA performance oversight. Benefits - Pay Range: $113,332.00 - $169,999.00 - Pay range may be based on a number of factors including market location, education, responsibilities, experience, etc.

• Own key tracks in Cluster Experience: reliability, performance, and user experience for distributed ML workloads. • Define product direction from problem discovery → design → delivery → adoption, working closely with engineering and research teams. • Drive cross-functional execution across compute, networking, storage, observability, and platform teams. • Perform deep customer research: interviews, analytics, and workload studies to identify bottlenecks across hardware, network, scheduler, and runtime. • Translate state-of-the-art ML papers ideas into practical, scalable product features for large GPU clusters. • Shape how users interact with clusters - from dashboards and notifications to partitioning, node management, and training observability.