Product Manager - Clinical Data Science & GenAI

Join us as we work to create a thriving ecosystem that delivers accessible, high-quality, and sustainable healthcare for all.

Position Summary: We’re looking for a Product Manager to help shape the future of athenahealth’s AI-Native Electronic Health Record. The Product Manager will lead the Clinical Data Science product area, developing the machine learning, generative AI, and evaluation capabilities that power clinical AI experiences. 

This role is based in Bangalore (Hybrid) and reports to the Product Management Director within athenaClinicals. 

About the Team: The Clinical Foundations team builds shared capabilities that support athenahealth’s electronic health record products. Team members partner with Product, Engineering, Design, Data Science, Clinical Informaticists, and Patient Safety professionals to deliver scalable, enterprise-grade AI product features. 

The team: 

• Integrates frontier lab large language models. 

• Builds in-house machine learning models. 

• Uses AI evaluation and observability platforms such as Arize, Kubeflow, and DataDog. 

• Uses Responsible AI practices to build solutions with the safety and efficacy required in a healthcare setting. 

• Develops AI capabilities that help reduce cognitive and administrative burdens in healthcare and ultimately improve patient outcomes. 

Essential Job Responsibilities 

• Define the product vision, business cases, and roadmap for the Clinical Data Science product area. 

• Serve as Product Owner for assigned Scrum teams by defining epics and user stories, prioritizing the backlog, and making informed trade-offs across customer value, scope, timing, and technical constraints. 

• Define the end-to-end product development lifecycle, including problem definition, requirements, user experience, objectives and key results, delivery, and measurement of customer and business outcomes. 

• Establish and monitor performance measures that provide visibility into product outcomes, risks, and opportunities for improvement. 

• Partner with Product, Engineering, Design, Data Science, Patient Safety, Legal, and business leaders to align product decisions with healthcare safety, regulatory, and operational needs. 

• Evaluate market conditions, customer needs, product dependencies, and business value to guide prioritization and product investment decisions. 

• Collaborate with Sales, Customer Success, and Product Marketing to develop clear customer-facing product information and service descriptions. 

• Support product teams in applying shared AI evaluation tools and governance practices across their business areas. 

• Share product management and responsible AI practices through coaching, documentation, and working sessions. 

• Contribute to planning and coordination across the broader Product Management organization. 

• Partner with product leadership to define use-case-specific evaluation strategies, benchmarks, success metrics, acceptance thresholds, and release criteria for generative AI capabilities. 

Expected Education & Experience 

• Bachelor’s degree required; a degree in Computer Science, Data Science, Business, or a related field is preferred. 

• Minimum 8+ years of Product Management or related experience. 

• Experience in healthcare or healthcare technology is preferred. 

• Practical experience developing generative AI solutions using large language models (LLMs), including prompt engineering, retrieval-augmented generation (RAG), model APIs, and analysis of model outputs. 

• Experience with LLM evaluation methods, including deterministic evaluations, LLM-as-Judge, subject matter expert annotation workflows, and online evaluations. 

• Experience with AI evaluation and observability platforms, such as Arize, Datadog, LangSmith, or Braintrust. 

• Experience designing or managing responsible AI solutions in regulated or high-impact environments, including safety testing, hallucination risk management, bias evaluation, auditability, data lineage, and compliance. 

• Knowledge of modern AI systems and practices, including large language models, RAG architecture, AI agents, observability, evaluation pipelines, model governance, prompt engineering, explainability, traceability, and production AI operations. 

• Experience working with Agile or Scrum product development teams. 

• Ability to analyze complex problems, use qualitative and quantitative evidence, and develop scalable product solutions. 

• Experience using AI tools such as Claude, Copilot, ChatGPT, and Figma Make to accelerate product development, including drafting requirements, synthesizing user feedback, creating specifications or prototypes, and analyzing data with appropriate human review.