Sr Manager, AI Engineer

At CVS Health, we're building a world of health around every consumer and surrounding ourselves with dedicated colleagues who are passionate about transforming health care. As the nation's leading health solutions company, we reach millions of Americans through our local presence, digital channels and more than 300,000 purpose-driven colleagues - caring for people where, when and how they choose in a way that is uniquely more connected, more convenient and more compassionate.

And we do it all with heart, each and every day.

The AI lead, leads the development and deployment of end-to-end AI and Machine Learning (ML) pipelines, ensuring that AI initiatives align with strategic business goals. This role requires a blend of deep technical expertise in AI technologies, architectural design principles, and strong leadership to guide cross‑functional teams. This high‑level, strategic role requires a professional to bridge the gap between business objectives and technical AI capabilities.

• Develop a comprehensive AI strategy and roadmap that supports business objectives and drives innovation.
• Design and develop scalable, secure, and resilient AI systems and infrastructure.
• Translate business needs and use cases into technical AI and ML solutions.
• Evaluate and select the most appropriate AI technologies, frameworks, and cloud services (e.g., AWS, Azure, GCP).

• Oversee the entire lifecycle of AI projects, from research and design to deployment and monitoring.
• Collaborate with data scientists and engineers to build robust data pipelines for AI model training and inference.
• Ensure the seamless integration of AI applications and ML models with existing IT infrastructure and business processes.
• Optimize AI systems for performance, scalability, and cost efficiency, and troubleshoot technical issues.

• Provide technical leadership and guidance to development teams, including AI engineers and software developers.
• Collaborate effectively with business stakeholders, product managers, and executives to communicate the potential, limitations, and strategic value of AI initiatives.
• Foster a culture of innovation and continuous improvement across AI teams.

• Ensure AI implementations comply with ethical standards, data privacy regulations (e.g., GDPR), and security best practices.
• Establish and enforce data governance policies for AI model development and data usage.
• Mitigate risks such as adversarial attacks and data poisoning.

• Stay up-to-date with the latest advancements in AI research, trends, and technologies.
• Recommend new methodologies and tools to improve the organization's AI capabilities.

• Extensive experience (5 - 7 years) in software development, data science, or as an AI/ML Engineer.
• Proven track record of designing, implementing, and deploying scalable AI solutions in a production environment.
• Demonstrated experience with cloud computing platforms (AWS, Azure, GCP) and MLOps practices.

• Programming
  
  Languages:
  
  Proficiency in Python is essential, along with experience in languages like R, Java, or Scala.
• AI/ML Frameworks: Expertise in machine learning and deep learning frameworks, such as Tensor Flow, PyTorch, and scikit‑learn.
• Data Technologies: Strong knowledge of big data technologies like Hadoop and Spark, as well as data processing and warehousing techniques.
• AI Concepts: Deep understanding of machine learning models, neural networks, natural language processing (NLP), and computer vision.

• Problem‑Solving: Exceptional analytical and critical thinking skills to address complex technical and business challenges.
• Communication: Strong ability to communicate complex technical concepts to both technical and non‑technical stakeholders.
• Leadership: Demonstrated leadership and project management capabilities to guide and mentor teams.
• Adaptability: A commitment to continuous learning to keep pace with the rapidly evolving field of AI.

• A Bachelor's degree in Computer Science, Data Science,…