Forward Deployed Product Manager

We are looking for a Forward Deployed Product Manager who can bridge the gap between product strategy, customer requirements, and technical execution. This role combines product management with hands-on customer engagement, requiring the ability to work closely with healthcare clients, understand complex business problems, and translate them into scalable AI-powered product solutions. The ideal candidate is comfortable operating in ambiguous environments, working directly with customers and engineering teams, and driving products from problem discovery through deployment and adoption.

The core responsibilities for the job include the following:

Customer Engagement and Problem Discovery:

• Work directly with customers and business stakeholders to understand their workflows, pain points, and operational challenges.
• Conduct discovery sessions to identify high-impact problems that can be solved through AI, automation, and data-driven products.
• Translate customer needs into clear product requirements, use cases, user stories, and acceptance criteria.
• Act as the primary product interface between customers, engineering, data science, and implementation teams.

Product Strategy and Roadmap:

• Define product vision, strategy, and roadmaps aligned with customer needs and business objectives.
• Prioritize features and initiatives based on customer impact, business value, technical feasibility, and scalability.
• Identify opportunities to convert customer-specific solutions into reusable product capabilities.
• Balance rapid customer delivery with long-term product architecture and maintainability.

AI and Data Product Development:

• Partner with AI/ML engineers, data scientists, data engineers, and software engineers to develop AI-powered solutions.
• Translate complex healthcare data problems into actionable product requirements and measurable outcomes.
• Understand the capabilities and limitations of machine learning, generative AI, LLMs, automation, and data pipelines.
• Define evaluation criteria, success metrics, and feedback loops for AI-driven product features.
• Work with engineering teams to address data quality, model performance, integration, and workflow automation challenges.

Forward Deployment and Implementation:

• Drive end-to-end execution of customer-facing product initiatives, from discovery and prototyping to deployment and adoption.
• Work closely with implementation and engineering teams to configure, integrate, test, and deploy solutions in customer environments.
• Troubleshoot product and workflow issues, identify root causes, and coordinate resolution with technical teams.
• Iterate rapidly based on real-world customer feedback and production performance.

Cross-functional Leadership:

• Collaborate with engineering, design, data science, sales, customer success, and leadership teams.
• Translate business priorities into executable plans and ensure alignment across stakeholders.
• Manage competing priorities, dependencies, risks, and delivery timelines.
• Communicate product decisions, progress, trade-offs, and outcomes effectively to technical and non-technical stakeholders.

Product Analytics and Business Impact:

• Define and track KPIs related to product adoption, customer outcomes, operational efficiency, accuracy, and ROI.
• Use customer feedback and product usage data to identify improvement opportunities.
• Measure the business impact of deployed solutions and continuously optimize product performance.

Requirements:

• 3-9 years of experience in product management, technical product management, solutions engineering, forward-deployed engineering/product roles, or related positions.
• Experience building and deploying enterprise software, data products, AI/ML products, or workflow automation solutions.
• Strong customer-facing experience, including requirements gathering, stakeholder management, and translating business problems into technical solutions.
• Proven ability to work closely with engineering teams and drive product execution from concept to deployment.
• Strong analytical, problem-solving, prioritization, and decision-making skills.
• Ability to navigate ambiguity and manage multiple initiatives in a fast-paced environment.
• Excellent communication and presentation skills.

Technical Skills and Preferred Experience:

• Working knowledge of SQL, APIs, data workflows, databases, and system integrations.
• Understanding of AI/ML concepts, generative AI, LLMs, RAG, and AI-powered automation.
• Familiarity with cloud platforms such as AWS, Azure, or GCP.
• Experience with product management tools such as Jira, Confluence, and product analytics platforms.
• Ability to collaborate on technical architecture discussions and understand engineering trade-offs.
• Experience in healthcare technology, health insurance, payer operations, provider data, or healthcare analytics is an advantage.
• Exposure to enterprise implementations, customer deployments, proof of concepts, and product experimentation is preferred.

What Success Looks Like:

• Customer problems are translated into clear, actionable product solutions.
• AI and data products are deployed successfully and deliver measurable business value.
• Customer-specific requirements are converted into scalable product capabilities wherever possible.
• Product adoption, operational efficiency, and customer satisfaction improve over time.
• Engineering and business teams remain aligned on priorities, timelines, and outcomes.

Ideal Candidate Profile:

• We are looking for someone who combines product thinking, technical depth, and customer-facing execution. The candidate should be able to engage directly with customers, understand complex workflows, collaborate with technical teams, and take ownership of delivering solutions that solve real business problems.
• The role is particularly suited to candidates who have worked in AI/data product management, enterprise SaaS, technical product management, solutions consulting with product ownership, or forward-deployed teams.
• Experience: Typically 5-10 years, depending on the depth of relevant product and technical experience.

Skills

AI, API, AWS, Azure, GCP, LLM, ML, RAG, SQL, machine learning, product