CVS Health is focused on building a world of health around every individual, aiming to simplify healthcare for communities. The Senior Manager, Machine Learning Engineering, is responsible for leading AI engineering teams to design and deploy scalable AI systems, ensuring they deliver business value while adhering to quality and performance standards.
Responsibilities:
- Lead, coach, and develop a team of AI Engineers, including team leads and senior engineers
- Establish clear goals, performance expectations, and development plans aligned with AI Engineering career frameworks
- Foster a culture of technical excellence, accountability, inclusion, and continuous improvement
- Support hiring, onboarding, and team capacity planning to meet delivery and growth objectives
- Provide regular feedback, mentorship, and succession planning for key technical and leadership roles
- Own delivery of multiple concurrent AI initiatives, ensuring solutions are scalable, reliable, and production‑ready
- Guide architecture and design decisions for AI systems, pipelines, and platforms in partnership with senior engineers
- Ensure best practices across model development, deployment, monitoring, and AI lifecycle management
- Balance near‑term execution with longer‑term technical health, platform evolution, and reuse
- Drive operational excellence, including reliability, performance, cost efficiency, and incident management
- Partner with product, data science, engineering, and business leaders to translate business needs into AI solutions
- Contribute to AI Engineering strategy, roadmaps, and prioritization decisions
- Communicate progress, risks, and trade‑offs clearly to leadership and stakeholders
- Influence cross‑functional teams and leaders without direct authority to achieve shared outcomes
Requirements:
- Bachelor's degree in Computer Science, Engineering, Data Science, or a related field (or equivalent experience)
- 5+ years of experience in software engineering, AI engineering, or applied AI roles
- 3+ years of people management experience or team lead, including leading senior technical contributors
- Demonstrated experience delivering and operating production AI systems at scale
- Strong understanding of AI engineering concepts such as model deployment, data pipelines, system reliability, and AI lifecycle management
- Proven ability to lead teams, influence stakeholders, and deliver results in complex environments
- Master's degree in a related technical field
- Experience leading AI platforms or shared services used by multiple teams
- Experience partnering with cloud, data, or security teams
- Familiarity with responsible AI, governance, and enterprise AI standards