About the role
AI Enablement Lead - Alaffia Health Return to jobs list AI Enablement Lead Job type: Full Time · Department: Finance · Work type: Hybrid · USD 140,000-180,000 / year New York, New York, United States Job details Application form About Alaffia & Our Mission Every year, U.S. health plans lose billions to improper payments and administrative waste. That wasted spending ultimately trickles down across the healthcare ecosystem, driving up costs for plans, providers, and patients alike. We’re here to change that paradigm. Alaffia is a new kind of claims operations partner for health plans. Using expert clinicians and transparent AI, we deliver deeper insights, smarter automation, and consistently better outcomes across the entire lifecycle of claims. With Alaffia, health plans can cut wasted spending more effectively than ever — and provide their members the most affordable care. We’re a high-growth, venture-backed Series B healthtech startup based in NYC and are actively scaling our company. Join us in helping to build a healthcare system that works better for everyone. *This position requires current authorization to work in the United States. Unfortunately, we are not in a position to sponsor work visas at this time.
About
the Role We’re a Series B company building AI software and delivering tech-enabled services to our customers — and we believe the companies that win the next decade will be the ones that rebuild themselves around AI first, internally, before asking anyone else to. We’re hiring an AI Transformation Lead to sit on the Business Operations team with a broad, executive-level mandate to do exactly that. Act as our internal “AI Leader” — the single accountable owner for how AI gets adopted, deployed, and scaled across every function in the company, reporting into the VP FInance and Operations with a direct line to the COO and CEO. Partner with functional leaders across GTM, Services, Product, Engineering, Finance, Biz Ops, and People to identify where AI creates the highest leverage — whether that’s automating manual workflows, compressing delivery cycles in our services org, improving gross and operating margins, or unlocking functional capacity without adding headcount. Operate as an org-wide leader-doer: set the vision and the 12-month roadmap, but also roll up your sleeves to prototype, deploy, and iterate on real solutions — this is not a slide-deck role. Build the operating system for how we run AI internally — the build-vs-buy decision rights, the governance guardrails that are compliant with HITRUST R2, SOC2 Type 2 and ISO/IEC 42001:2023, the rollout playbooks and change management, and the measurement standards. Make us a visible exemplar of an AI-native company, both to prospects evaluating our software and to the talent market — what we do internally should be a proof point for what we sell. We should “eat our own cooking”. What You'll be Doing Own the enterprise AI transformation roadmap end-to-end, sequencing high-ROI near-term wins (RAG over internal knowledge, workflow automation, GTM and services copilots) alongside the longer-horizon investments in agentic systems and structural process redesigns. Run a disciplined opportunity identification process through interviews with function leaders, map current-state workflows, quantify time and cost, and prioritize use cases by expected ROI, feasibility, and strategic fit. Build, test, and deploy AI solutions hands-on where it’s faster to do so — prompt engineering, lightweight agents, automations, low code workflows, LLM-based tooling, custom integrations. Work with cross functional stakeholders to develop and defend build-vs-buy decisions with clear business cases, tracking vendor evaluations, pilots, and full deployments against pre-committed KPIs (hours saved, cycle time reduced, NRR impact, margin expansion, deflection rate, etc.) Drive adoption — design enablement programs, office hours, champions networks, and change management so the tools actually get used and the value is realized. Partner with Services leadership to embed AI into our customer-facing delivery motion — reducing cost-to-serve, improving quality, and driving gross margin expansion as we scale. Establish responsible-AI guardrails in partnership with Legal, Security, and Engineering — data handling policies, model risk review, acceptable-use standards, and SOC 2 / HIPAA customer contract alignment, help to define
