AI Fellow

HumanaLouisville, KY
$208,500 - $286,700Remote

About The Position

The AI Strategy Fellow is a senior, individual contributor responsible for shaping and advancing the enterprise AI strategy for a Fortune 40 healthcare organization. This role uniquely blends strategic vision, business-outcome orientation, hands-on technical prototyping, compelling executive storytelling, and deep industry awareness — operating at the intersection of enterprise technology strategy, applied AI, and business transformation. The Fellow partners directly with Enterprise AI leadership, architecture teams, and senior business executives to drive a multi-year AI roadmap, translate that roadmap into tangible business value, and champion a culture of prototype-driven innovation. Unlike traditional leadership roles, the Fellow influences direction through expertise, credibility, and demonstration rather than direct team or product ownership. This role is primarily an Individual Contributor and reports to the VP, Enterprise AI Strategy & Governance.

Requirements

  • 10+ years of experience in AI/ML, advanced analytics, or enterprise technology strategy, with increasing technical depth.
  • Proven experience shaping or advising on enterprise-scale AI platforms, architectures, or transformations.
  • Demonstrated ability to influence C-level and senior executives on complex technical and strategic topics.
  • Experience working in highly matrixed Fortune 100 environments or equivalent scale.
  • Track record of personally building prototypes or proof-of-concepts that influenced strategic or investment decisions at the enterprise level.
  • Demonstrated excellence in executive storytelling and strategic communication, including experience presenting to C-suite, board, or equivalent audiences.
  • History of translating external industry trends into internal strategy adjustments or new capability investments.
  • Deep understanding of: Machine learning lifecycle and MLOps, Generative AI and LLM ecosystems, Data architectures and cloud platforms (e.g., Azure, AWS, GCP)
  • Hands-on familiarity with: Model development frameworks (e.g., PyTorch, TensorFlow), LLM orchestration frameworks and tooling, Vector databases, embeddings, and retrieval architectures, Rapid prototyping tools and environments (e.g., Jupyter notebooks, Streamlit, Gradio, or equivalent), API-first experimentation with LLM providers (OpenAI, Anthropic, open-source models), Low-code/no-code AI platforms for fast demonstration builds
  • Strong grasp of system design, scalability, and distributed architectures.
  • Exceptional written and verbal communication skills, with the ability to craft narratives that resonate across technical and non-technical audiences.
  • Strong visual communication and data storytelling capabilities.
  • Ability to operate with influence and credibility in highly matrixed environments without positional authority.

Responsibilities

  • Lead the development and evolution of the multi-year enterprise AI strategy, including GenAI, machine learning, and emerging AI paradigms.
  • Own the articulation and maintenance of the multi-year enterprise AI roadmap, ensuring it evolves with business priorities, technology maturity, and competitive landscape shifts.
  • Primary architect of Humana's AI strategy, defining necessary technology investments, and driving transparency in prioritization and planning.
  • Develop and maintain a capability-to-outcome mapping framework that explicitly interlocks foundational AI platform capabilities (e.g., model orchestration, data pipelines, MLOps) to prioritized business use cases and measurable outcomes.
  • Provide domain expertise on ecosystem design, integration patterns across enterprise systems, and partner with AI platform engineering on scaled capabilities.
  • Shape reference architectures and scalable platform models that enable reuse, interoperability, and rapid experimentation.
  • Advise on LLM strategy, including model selection, orchestration approaches, RAG architectures, and optimization techniques.
  • Personally build and lead rapid prototypes and proof-of-concepts that demonstrate the feasibility and business value of emerging AI capabilities — serving as a catalyst for organizational buy-in and faster decision-making.
  • Champion a prototype-driven thinking culture across the AI organization, establishing lightweight frameworks for fast experimentation, learning, and iteration.
  • Translate abstract strategic concepts into tangible, working demonstrations that accelerate stakeholder alignment and de-risk enterprise-scale investments.
  • Leverage hands-on fluency with modern AI tooling (LLM APIs, orchestration frameworks, low-code/no-code platforms) to stay grounded in technical reality and credibly advise on implementation feasibility.
  • Design and drive frameworks for scaling AI adoption across business units, ensuring alignment to measurable business outcomes.
  • Identify and prioritize high-value AI use cases across the enterprise, balancing feasibility, risk, and impact.
  • Design and own frameworks for value tracking, including cost reduction, productivity gains, and revenue enablement tied to AI initiatives.
  • Partner with business and technical leaders to accelerate transition from pilots to enterprise-scale deployment.
  • Craft compelling, board-ready narratives that translate complex AI strategies, technical architectures, and innovation pipelines into clear, outcome-oriented stories for C-suite and board audiences.
  • Develop and maintain a suite of executive communication assets — strategy briefs, roadmap visualizations, value-realization dashboards, and investment narratives — that keep leadership aligned and informed.
  • Serve as a storytelling partner to Enterprise AI leadership, helping frame AI initiatives in the language of business transformation, member outcomes, and competitive differentiation.
  • Distill technical complexity into simple, memorable frameworks that enable non-technical executives to make informed decisions on AI investments and priorities.
  • Serve as a senior advisor on critical AI-related decisions, including: buy vs. build vs. partner strategies; model architecture and tooling choices; platform investments and vendor selection.
  • Provide objective, data-driven recommendations grounded in industry best practices and emerging trends.
  • Contribute to governance forums (e.g., AI review boards) with deep technical insight and independent perspective.
  • Partner with governance and risk functions to advance responsible AI practices, including fairness, explainability, and compliance.
  • Provide technical input into model risk management frameworks, evaluation standards, and monitoring approaches.
  • Define and champion guardrails for safe and ethical scaling of generative AI capabilities.
  • Act as a trusted advisor to senior executives, translating highly technical AI concepts into clear business implications.
  • Influence roadmaps across Enterprise AI, Cloud, Data, and Security teams without direct ownership.
  • Continuously scan and synthesize the external AI landscape — including emerging models, tooling, competitive moves, regulatory developments, and academic research — and translate insights into actionable recommendations that shape internal roadmaps and investment priorities.
  • Establish and maintain a structured mechanism (e.g., quarterly trend briefings, competitive intelligence digests) for bringing outside-in perspectives to Enterprise AI leadership and key stakeholders.
  • Build and leverage an external network of AI practitioners, researchers, and industry analysts to ensure the organization remains at the forefront of applied AI innovation.
  • Represent the organization in selective external forums as a thought leader in enterprise AI strategy and adoption.
  • Use your skills to make an impact

Benefits

  • medical
  • dental
  • vision
  • 401(k) retirement savings plan
  • time off (including paid time off, company and personal holidays, paid parental and caregiver leave)
  • short-term and long-term disability
  • life insurance
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