Company Introduction

Availity is one of the leading health information networks in the United States, processing more than 4 billion transactions annually and connecting more than two million healthcare providers and over two thousand technology partners to health plans nationwide. Our teams of technology, business, and customer service professionals in Bangalore, India, are working together to transform healthcare delivery in the United States through innovation and collaboration. Our technologists help develop cutting-edge revenue cycle solutions that help hospitals, health systems, and physicians maximize payments and optimize their workflows.

Job Description

Roles & Responsibilities

Role Overview 

We are seeking a visionary, entrepreneurial product leader to identify, incubate, and scale new growth opportunities. The Director, Product - Emerging Solutions & Innovation will operate at the intersection of customer needs, data, artificial intelligence, healthcare technology, and platform innovation to create differentiated products and new sources of value.  

This role is accountable for taking products from 0-to-1: discovering high-value problems, forming investment hypotheses, rapidly prototyping solutions, launching pilots, validating product-market fit, and transitioning successful concepts into scalable products and sustainable business lines.  

The ideal candidate combines strategic product leadership with a hands-on builder mindset. They must be comfortable navigating ambiguity, making evidence-based investment decisions, and mobilizing cross-functional teams to convert emerging technologies and white-space opportunities into measurable customer and business outcomes.  

SUCCESS PROFILE  A product innovator who has repeatedly transformed unproven ideas into validated, market-ready products through disciplined experimentation, rapid learning, and commercial execution.  

Key Responsibilities  

1. Product Innovation & Opportunity Development  

• Identify and prioritize emerging customer needs, market shifts, technology trends, and white-space opportunities that align with enterprise strategy and growth objectives.  

• Define compelling opportunity narratives, product theses, and value propositions grounded in customer evidence, market attractiveness, strategic fit, and differentiated advantage.  

• Build investment cases that clearly articulate the problem, target customer, addressable opportunity, solution hypothesis, expected value, key assumptions, risks, and funding requirements.  

• Maintain an innovation portfolio that balances near-term experiments with longer-term strategic bets, using clear criteria to start, continue, pivot, scale, or stop initiatives.  

2. Product Incubation and 0-to-1 Execution  

• Own the complete incubation lifecycle from concept and discovery through prototype, MVP, pilot, product-market fit validation, commercialization, and scale transition.  

• Translate ambiguous opportunities into structured discovery plans, testable hypotheses, learning agendas, and sequenced experiments.  

• Apply Lean Startup, Design Thinking, and outcome-based product practices to accelerate learning while reducing investment and delivery risk.  

• Establish stage-gate governance with evidence-based decisions, explicit exit criteria, and transparent recommendations for continued investment.  

• Remain close to the work by shaping product concepts, reviewing prototypes, engaging design partners, interpreting pilot results, and resolving critical product trade-offs.  

3. AI, Data and Emerging Technology Products  

• Define product strategies for AI-enabled, data-driven, analytics, automation, and platform capabilities that solve meaningful customer and business problems.  

• Partner with Engineering, Architecture, Data Science, Security, Privacy, Legal, and Compliance teams to assess technical feasibility, data readiness, model performance, operational needs, and enterprise risk.  

• Design data products with clear data sourcing, quality, interoperability, governance, insight delivery, and monetization considerations.  

• Define AI product requirements beyond model accuracy, including workflow integration, explainability, human oversight, reliability, monitoring, adoption, and measurable business impact.  

• Promote responsible AI practices by incorporating privacy, security, fairness, transparency, accountability, regulatory, and customer trust considerations throughout the product lifecycle.  

4. Rapid Prototyping, Experimentation and Pilots  

• Champion rapid prototyping using modern design, low-code, AI-assisted, and engineering approaches to make ideas tangible and test assumptions quickly.  

• Lead design sprints, customer co-creation sessions, proof-of-concepts, concierge tests, MVPs, and controlled pilots with clear learning objectives.  

• Define success measures before each experiment, including customer desirability, usability, technical feasibility, operational viability, commercial potential, and strategic value.  

• Build strong design-partner relationships and establish mechanisms to gather, synthesize, and act on qualitative and quantitative feedback.  

• Create a high-learning-velocity environment where teams test critical assumptions early, share evidence transparently, and adapt direction rapidly.  

5. Commercialization and Scale  

• Partner with Sales, Marketing, Customer Success, Finance, Operations, and Legal to define market positioning, target segments, pricing, packaging, launch readiness, and go-to-market plans.  

• Develop adoption and growth models that connect product usage to customer outcomes, revenue potential, retention, efficiency, or strategic differentiation.  

• Lead pilot-to-production decisions and create practical scale plans covering technology, operations, support, enablement, compliance, and financial sustainability.  

• Guide successful incubated products through a disciplined transition to a scaled product organization while preserving strategic intent, customer insight, and outcome accountability.  

• Monitor post-launch performance and continuously improve the product, proposition, and operating model based on evidence.  

6. Product Strategy, Portfolio and Outcome Management  

• Set the vision, strategic narrative, objectives, and multi-quarter roadmap for the emerging product portfolio.  

• Define north-star outcomes, leading indicators, guardrail metrics, and learning metrics for each initiative.  

• Use customer data, product analytics, market intelligence, and financial evidence to prioritize opportunities and guide portfolio investment.  

• Balance speed with quality and risk, making explicit trade-offs among customer value, business impact, strategic alignment, technical feasibility, and time to learning.  

• Communicate portfolio health, evidence, risks, decisions, and recommended actions to executive stakeholders with clarity and candor.  

7. Cross-Functional and Executive Leadership  

• Create shared direction across Product, Engineering, UX, Data, Architecture, Sales, Marketing, Operations, Finance, Legal, Security, and executive leadership.  

• Influence without relying on authority, resolve competing priorities, and secure the sponsorship, funding, talent, and operating support needed to advance promising opportunities.  

• Act as the single-threaded product leader for incubation decisions and ensure accountability for outcomes across participating teams.  

• Build trusted relationships with customers, partners, industry experts, and ecosystem participants to strengthen discovery and accelerate validation.  

8. Team Leadership and Product Craft  

• Lead, coach, and develop product managers responsible for emerging products, fostering strategic thinking, customer obsession, commercial acumen, experimentation, and ownership.  

• Build reusable incubation playbooks, templates, metrics, decision forums, and knowledge-sharing practices that improve innovation effectiveness across the organization.  

• Create a culture that values evidence over opinion, progress over perfection, and learning over activity while maintaining high standards for product quality and ethical decision-making.  

• Attract and retain diverse, high-performing talent capable of operating across strategy, discovery, technology, and commercialization.  

Required Qualifications  

• 12+ years of progressive product management experience, including significant leadership responsibility for product strategy, discovery, delivery, and business outcomes.  

• Demonstrated success creating and launching one or more 0-to-1 products, with direct ownership from opportunity identification through validation and commercialization.  

• Experience developing data products, AI-enabled products, analytics solutions, intelligent automation, or technology platforms.  

• Hands-on experience with rapid prototyping, MVP development, customer pilots, design-partner programs, and iterative validation.  

• Ability to translate uncertain opportunities into structured hypotheses, experiments, product decisions, and investment recommendations.  

• Strong commercial and financial acumen, including business-case development, market sizing, pricing, packaging, monetization, and go-to-market planning.  

• Proven ability to lead complex cross-functional initiatives and influence senior executives, technical leaders, customers, and commercial stakeholders.  

• Excellent written, verbal, storytelling, and executive communication skills, with the ability to make complex concepts clear and actionable.  

• Experience hiring, coaching, and developing product management talent.  

Preferred Qualifications  

• Bachelor's degree in Engineering, Computer Science, Information Systems, Data Science, or a related technical discipline; an MBA or equivalent advanced business qualification is strongly preferred.  

• Experience in healthcare technology, enterprise SaaS, platform products, payer-provider workflows, interoperability, or regulated data environments.  

• Experience working in a startup, corporate innovation lab, venture studio, emerging-products group, or another environment where teams created new products under uncertainty.  

• Working knowledge of generative AI, machine learning, predictive analytics, data platforms, APIs, cloud-native architectures, and modern product development practices.  

• Experience establishing governance and operating models for AI and data products, including privacy, security, model risk, and responsible AI considerations.  

• Evidence of successfully stopping or pivoting low-potential initiatives based on learning, as well as scaling validated opportunities.  

Measures of Success  

• Quality and strategic relevance of the innovation pipeline and clarity of portfolio investment decisions.  

• Speed from opportunity identification to prototype, pilot, validated learning, and market launch.  

• Percentage of critical assumptions tested before significant investment and quality of stage-gate evidence.  

• Pilot conversion, product adoption, customer value realization, revenue or efficiency impact, and progress toward product-market fit.  

• Effectiveness of cross-functional alignment, executive decision-making, and transition of successful products into scalable ownership.  

• Growth, engagement, and innovation capability of the product team.  

What Success Looks Like in the First 12 Months  

• Establish a clear emerging-products strategy, opportunity thesis, prioritization model, and incubation operating cadence.  

• Build a qualified portfolio of high-value AI, data, and platform opportunities supported by customer and market evidence.  

• Advance priority concepts through rapid prototypes and design-partner validation, with explicit decisions to scale, pivot, or stop.  

• Launch one or more pilots with defined learning goals, operational readiness, success metrics, and commercialization pathways.  

• Create strong executive visibility into portfolio health, investment needs, risks, learning, and expected business value.  

• Raise organizational capability in 0-to-1 product development through coaching, reusable practices, and disciplined experimentation.  

Eligibility

Video Camera Usage:

Availity fosters a collaborative and open culture where communication and engagement are central to our success.  As a remote first company, we are also camera-first and provide all associates with camera/video capability to simulate the office environment. If you are not able to use your camera for all virtual meetings, you should not apply for this role.

Having cameras on helps create a more connected, interactive, and productive environment, allowing teams to communicate more effectively and build stronger working relationships.  The usage of cameras also enhances security and protects sensitive company information. Video participation is required to ensure that only authorized personnel are present in meetings and to prevent unauthorized access, data breaches, preventing social engineering, or the sharing of confidential information with non-participants.