exponential
Principal AI Product Lead — Healthcare Payment Accuracy & Decision Intelligence
Location: Hyderabad
About Us
Rialtic and Exponential AI recently merged to create a unified platform spanning the full healthcare claims lifecycle — combining Rialtic's rules-based payment accuracy platform with Exponential AI's Enso platform of prebuilt Decision Agents. Headquartered in Atlanta, the combined company serves leading U.S. health plans and provider systems, with a dedicated R&D center in Hyderabad, India.
Our mission is to help payers and providers make healthcare meaningfully more affordable for American families and employers. We do this by embedding agentic AI systems — intelligent decision agents — directly into claims and clinical workflows to automate reviews, identify payment issues, and support real-time decision-making, while delivering transparent, predictable, and explainable machine decisions in real time.
About the Role
We're looking for a Principal AI Product Lead to drive product strategy and execution for our unified payment accuracy and decision intelligence platform. You'll own one or more flagship areas across our product suite — spanning claims adjudication, coordination of benefits, claims audit, payment integrity, contract management, and utilization management — and shape how AI Decision Agents are productized, scaled, and adopted by the largest payers and provider systems in the country.
This is a senior individual contributor role with executive visibility. You'll be a critical voice in defining how the combined Rialtic + Exponential AI roadmap evolves post-merger, with the autonomy to set direction and the responsibility to deliver measurable client outcomes.
What You'll Do
  • Own end-to-end product strategy and roadmap for AI-powered offerings across the claim lifecycle, from prepay editing to real-time decision intelligence during and after adjudication.
  • Productize and scale Decision Agents on the Enso platform — defining which agents to build, how they compose into client-facing solutions, and how they integrate with Rialtic's editing system and customers' legacy infrastructure.
  • Translate complex payer and provider problems — payment integrity leakage, claims rework, prior auth bottlenecks, contract compliance, audit defensibility — into well-scoped, high-ROI AI product opportunities.
  • Partner closely with AL and ML engineering, data science, and platform teams to define agent requirements, evaluation criteria, and acceptable accuracy and explainability thresholds for production deployment.
  • Engage with health plan executives, provider finance executives, payment integrity leaders, and clinical operations teams to validate problems, co-design solutions, and drive adoption.
  • Establish frameworks for responsible and explainable AI in claims and clinical decisioning — bias auditing, human-in-the-loop review, audit trails, and continuous learning from feedback loops.
  • Define success metrics that matter to clients: dollars saved, leakage prevented, cycle time reduced, auto-adjudication rates, false positive rates, and provider abrasion.
  • Serve as a thought partner to the leadership on portfolio strategy, M&A integration priorities, and category positioning in a rapidly consolidating market.
  • Mentor product managers, engineers across the combined organization and help shape product culture during this pivotal post-merger phase.
What You Bring
  • 10–15 years of product management experience, with a substantial portion building enterprise products in the U.S. healthcare payer and/or provider markets.
  • Expertise in at least one of: payment integrity, claims editing and adjudication, payment accuracy, utilization management, revenue cycle management, contract management, or healthcare audit.
  • Proven track record of shipping AI/ML-powered products at enterprise scale — ideally including agentic AI, decision intelligence, or workflow automation deployed at health plans or large provider systems.
  • Direct experience with Decision Agents, agentic AI architectures, or LLM-powered enterprise workflows in healthcare administration.
  • Technical literacy to engage substantively with AIML and platform engineers on agent architecture, model evaluation, real-time inference at scale, integration with legacy core admin systems, and trade-offs between deterministic rules and learned models.
  • Strong fluency in healthcare regulation and compliance: HIPAA, state-level payer regulations, CMS guidance, and emerging AI governance standards relevant to administrative AI.
  • Excellent written and verbal communication; you can move fluidly between a payment integrity leader, an AIML engineer, and a board deck.
  • Bachelor's degree required; advanced degree a plus.
Nice to Have
  • Knowledge of healthcare claims data (837/835, EDI), coding systems (ICD-10, CPT, HCPCS, DRG), payer policies, NCCI edits, and the operational realities of claims processing.
  • Prior product role at a payment integrity vendor (e.g., Cotiviti, ClaimsXten/Lyric, EXL, Optum, Zelis) or at a major health plan's payment integrity, SIU, or claims operations team.
  • Experience integrating with major core admin platforms (Facets, QNXT, HealthEdge, HealthRules) and provider EHRs (Epic, Oracle Health/Cerner).
  • Background leading product through a post-merger integration or platform consolidation.
  • Familiarity with FHIR, X12, and modern healthcare interoperability standards.

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