VP, AI Platform Engineering

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 AI is no longer a specialized toolset—it is a foundational enterprise capability. As the Vice President of AI Platform, you are forward-thinking and execution obsessed. You will build, operate, and continuously evolve the company’s enterprise AI platform. This leader will be responsible for establishing a reusable, extensible, and secure foundation for all AI development—spanning traditional machine learning, generative AI, and agentic AI.
The VP of AI Platform will empower developers, data scientists, and business units with tools and infrastructure that make AI innovation fast, safe, and scalable across the enterprise. This is a platform leadership role that sits at the core of Humana’s long-term technology strategy.

               

Key Responsibilities

• Build the Enterprise AI Platform
  Architect a secure, modular, cloud-native AI platform that supports the full lifecycle of AI development—from data ingestion to model deployment and integration. Prioritize reusable components such as feature stores, model registries, vector databases, embedding libraries, RAG pipelines, agent frameworks, and fine-tuning workflows.

• Design for Reusability and Extensibility
  Ensure the platform enables composability and cross-team reuse through well-defined APIs, standard schemas, common solution patterns, and plug-in interfaces. Architect for rapid integration of future AI capabilities without costly refactoring.

• Operate at Scale with Reliability and Security
  Lead the operational support of the platform as a high-availability, multi-tenant service. Ensure enterprise-grade SLAs, robust observability, failover resilience, and built-in security controls. Optimize for performance and cost across diverse AI workloads—including LLM inference, agentic workflows, and batch model training.

• Deliver World-Class Developer and Data Scientist Experience
  Provide intuitive APIs, self-service tools, and seamless CI/CD integration that streamline experimentation, deployment, and monitoring. Prioritize developer productivity, data scientist autonomy, and frictionless onboarding as critical platform KPIs.

• Establish Governance and Responsible AI Guardrails
  Build native support for model lineage tracking, version control, drift detection, audit logging, and compliance automation. Align platform policies with responsible AI standards and regulatory frameworks. Embed safety, fairness, transparency, and explainability into the platform’s foundation.

• Continuously Evolve with the AI Ecosystem
  Lead the evaluation and responsible adoption of emerging technologies—including open-source LLMs, synthetic data platforms, memory-augmented agents, and privacy-preserving machine learning. Maintain a forward-compatible architecture that allows rapid exploration without destabilizing production systems.

• Drive Adoption and Strategic Alignment Across the Enterprise
  Collaborate across the enterprise to ensure platform capabilities align with real-world use cases. Act as a multiplier by promoting standards, fostering internal communities of practice, and scaling success patterns across the enterprise.

Use your skills to make an impact
 

Required Qualifications:

• Master’s degree in computer science, Machine Learning, or a related quantitative discipline.

• 10+ years leading platform teams focused on ML or AI in large enterprise.

• Proven track record in building enterprise-grade AI platforms at scale, with deep understanding of machine learning infrastructure, distributed model training, LLMOps, agentic architectures, and real-time inference systems.

• Strong cloud-native engineering background (AWS, Azure, and GCP), with expertise in Kubernetes, containerization, and modern DevSecOps practices.

• Demonstrated experience aligning AI platform strategy with enterprise business goals and delivering measurable business value.

• Demonstrated success enabling high developer productivity and reusable AI assets across complex, regulated environments.

• Demonstrated ability to drive platform adoption and cultural change in a complex, matrixed organization.

• Exceptional oral and written communication skills

Preferred

• Doctorate degree in Computer Science, Machine Learning, or a related quantitative discipline.

• Experience in highly regulated industries such as healthcare, life sciences, or financial services, where reliability, safety, and auditability are critical.

• Thought leadership in Responsible AI, AI governance, or open-source AI communities.

Travel: While this is a remote position, occasional travel to Humana's offices for training or meetings may be required.

Scheduled Weekly Hours

40

About us
 Humana Inc. (NYSE: HUM) is committed to putting health first – for our teammates, our customers and our company. Through our Humana insurance services and CenterWell healthcare services, we make it easier for the millions of people we serve to achieve their best health – delivering the care and service they need, when they need it. These efforts are leading to a better quality of life for people with Medicare, Medicaid, families, individuals, military service personnel, and communities at large.

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Equal Opportunity Employer

It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.