Senior Manager – AI Engineer

Job not on LinkedIn

🕒 Yesterday

🦌 Connecticut – Remote

🦌 Connecticut – Remote

💵 $130.3k - $260.6k / year

⏰ Full Time

🟠 Senior

🤖 AI Engineer

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CVS Health

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1963

⚕️ Healthcare Insurance

🛒 Retail

🧘 Wellness

Healthcare Insurance • Retail • Wellness

CVS Health is a leading American healthcare company dedicated to improving health access and affordability. The company focuses on a comprehensive approach that includes health services, health insurance, and pharmacy benefits management. Through its subsidiaries, such as Aetna and CVS Caremark, CVS Health offers a range of services that facilitate wellness, condition management, and affordable prescription drug coverage. CVS Health operates neighborhood pharmacies, provides mail-order pharmacy services, and manages specialty medication programs, aiming to make healthcare convenient and accessible for everyone. Driven by a mission to connect people with essential care services, CVS Health is committed to fostering healthier communities and supporting the wellbeing of all individuals.

📋 Description

• Define the technical vision and architecture for AI and ML solutions, including LLM based applications, conversational voice AI, chatbot platforms, and AI augmented BI systems • Oversee development of training data pipelines and datasets for fine tuning, evaluation, and inference at enterprise scale • Establish enterprise standards for model performance monitoring, drift detection, retraining, and lifecycle governance • Drive implementation of vector embeddings, semantic search, and AI orchestration frameworks • Provide engineering leadership for backend services (APIs, microservices) enabling scalable AI capabilities across the enterprise • Oversee development of scalable data pipelines supporting ingestion, transformation, and real time inference workloads • Drive integration of AI capabilities into enterprise platforms, including customer facing voice and chat systems and internal analytics environments • Ensure solutions meet enterprise standards for scalability, reliability, performance, and security • Define and govern model lifecycle management practices including versioning, deployment, rollback, and compliance • Lead the development of enterprise AI platforms and infrastructure for model hosting, orchestration, and scaling • Establish CI and CD standards and deployment frameworks for AI systems across engineering teams • Build and oversee observability layers to monitor system performance, model behavior, and operational health • Set direction for AI safety and responsible AI practices, including guardrails for bias mitigation, hallucination reduction, and policy adherence • Set and drive enterprise AI strategy aligned to technology vision, platform evolution, and long-term organizational priorities • Lead alignment across a highly matrixed organization, influencing engineering, product, analytics, and business leadership • Serve as a trusted advisor to executive leadership, communicating AI strategy, technical trade-offs, risks, and business impact • Own AI investment strategy, including prioritization, funding alignment, and resource allocation across initiatives • Drive enterprise-wide AI adoption by establishing scalable enablement models across engineering and business teams • Define and execute capability uplift strategies, including upskilling engineers, promoting best practices, and enabling self-service AI development • Champion innovation by introducing emerging AI technologies, tools, and solution patterns to accelerate experimentation and delivery • Establish and govern AI vendor and partner strategy, including evaluation, selection, negotiation, and performance oversight • Oversee SOW development and partner with product and finance leadership to manage budgets, forecasts, and investment planning • Act as the primary interface between engineering and executive leadership, ensuring transparency, accountability, and delivery outcomes • Influence enterprise architecture, engineering standards, and AI governance frameworks

🎯 Requirements

• Extensive experience leading engineering or AI and ML organizations within large scale enterprise environments • Demonstrated ability to operate at a senior leadership level, influencing executive stakeholders and enterprise strategy • Proven experience owning or driving technology investment strategy, budgeting, and resource allocation • Experience leading transformation initiatives and driving adoption of emerging technologies across organizations • Experience building and scaling engineering platforms, systems, or organizational capabilities • Experience within healthcare, health insurance, or regulated healthcare environments, with strong understanding of compliance, data privacy, and domain specific challenges • Deep expertise in software engineering fundamentals (SDLC, architecture, distributed systems design) • Proficiency in one or more programming languages (Python, C#, Java, etc.) • Experience building data pipelines and working with structured and unstructured data • Hands on experience with AI and ML frameworks, platforms, or applied AI systems • Strong understanding of APIs, microservices, and cloud-based architectures • Experience with cloud platforms (Azure, AWS, or GCP) • Familiarity with databases (SQL / NoSQL) • Experience leading vendor strategy, including evaluation, selection, and delivery governance. • Experience defining or leading enterprise AI strategy or platforms at scale (Preferred) • Hands on experience with LLMs, prompt engineering, or fine-tuning models (Preferred) • Experience building conversational AI (voice and chat) ecosystems (Preferred) • Experience with AI augmented analytics or business intelligence platforms (Preferred) • Experience with vector databases, embeddings, and semantic search (Preferred) • Familiarity with MLOps, observability, and model monitoring frameworks (Preferred) • Experience implementing responsible AI, governance, and risk management practices (Preferred) • Experience operating at Director or VP level or equivalent leadership scope (Preferred) • Experience in healthcare, analytics, or enterprise data platforms (Preferred) • Exposure to tools such as Databricks, Spark, or real time analytics systems (Preferred)

🏖️ Benefits

• medical, dental, and vision coverage • paid time off • retirement savings options • wellness programs • comprehensive benefits package