Lead Director - Software Engineering (Health100 Platform)

CVS Health•Work At Home-Texas, MA

2d•$144,200 - $288,400

About The Position

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Health100 is America's trusted front door to health and care. The Health100 platform integrates any participating health plan, PBM, pharmacy (retail and specialty), provider, digital health point solution provider, and employer, and addresses the top health care challenges for the consumer. We're looking for a hands-on, passionate engineering leader to join a high-energy, mission-driven team on the forefront of digital health innovation — reinventing how consumers engage with their health through cross-platform apps, open APIs, and a growing multi-agent AI system. As Lead Director of Software Engineering, you will own the strategic vision, architecture, and execution of a platform roadmap that spans traditional distributed systems and applied generative AI — from agent orchestration to LLM infrastructure decisions. As a key strategic leader, you'll partner deeply with stakeholders across Health100 and CVS Health to understand consumers, the current product landscape, operational needs, and business goals — developing long-term visions, technical strategies, and roadmaps for both platform engineering and AI-driven consumer experiences. Design thinking is at the center of everything you do, ensuring consumer centricity guides how agents, apps, and APIs come together to deliver the right value to the right person at the right time.

Requirements

12+ years of software engineering experience, including 5+ years leading managers and senior engineers in Agile, cloud-native environments.
Proven delivery of large-scale, multi-team engineering programs spanning backend platforms, native Mobile and cross-platform apps (e.g., Flutter, React Native, or similar), and increasing AI-driven features — owning strategy through execution in fast-paced digital or healthcare technology organizations.
Strong technical depth in distributed systems and cloud-native architectures, including microservices (Java/Spring Boot, Python), DevOps (CI/CD, Kubernetes/Docker), and cloud platforms (GCP preferred).
Demonstrated success building and scaling high-performing engineering organizations, including distributed teams (onshore/offshore/nearshore) and vendor partnerships.
Executive-level communication and influence skills, with hands-on or applied experience (1+ year) delivering AI-enabled or generative AI-integrated software — ideally including agent-based architectures, tool-use/function calling, or protocols like MCP, not just API-level LLM calls.

Nice To Haves

Proven experience hiring and leading high-performing, distributed engineering teams, including multi-site and fully remote models.
Practical experience with multi-agent AI systems — designing supervisor/sub-agent patterns, inter-agent routing logic, and horizontal AI capabilities like personalization and next-best-action.
Experience evaluating LLM infrastructure tradeoffs — hosted models (e.g., Gemini) vs. open-source (e.g., Qwen, Mistral, Llama) vs. on-device/edge models (e.g., Apple Foundation Models, Gemma) — for cost, latency, and quality.
Demonstrated data-driven problem solving, using quantitative analysis (including AI/agent-specific metrics) to guide decisions and improve outcomes.
Hands-on experience defining, tracking, and analyzing KPIs to measure engineering productivity, delivery health, and project success — extended to AI/agent observability (tracing, evals, prompt versioning) where applicable.
Experience delivering healthcare or wellness technology solutions, working effectively with both onshore and offshore vendor teams.

Responsibilities

Define and drive multi-team product and technical roadmaps spanning cross-platform app development, platform APIs, and AI agent capabilities.
Set architectural direction on modern topics — multi-agent orchestration (supervisor/sub-agent, agent-to-agent), tool/data integration via protocols like MCP, RAG pipelines, and LLM infrastructure (hosted vs. open-source, on-device models) — alongside traditional distributed systems investments.
Align engineering investment across backend, mobile/web, and AI/ML disciplines with business outcomes.
Establish scalable engineering standards and operational frameworks across full-stack app development and AI agent systems.
Build risk management practices that account for AI-specific concerns — model drift, hallucination/safety guardrails, data privacy, prompt injection, and agent routing accuracy — alongside standard reliability and quality practices.
Drive observability and evaluation practices for both traditional systems (uptime, latency) and AI agents (accuracy, cost per interaction, tracing, evals).
Lead, mentor, and grow engineering managers and senior engineers across backend, cross-platform app, and applied AI/agent disciplines.
Own hiring, performance management, career development, and succession planning, building fluency in AI-assisted and agentic development practices across the org.
Foster a culture of accountability and high performance amid fast-evolving tooling and standards.
Partner closely with Product, Business, Architecture, Design, Security, and executive leaders to translate strategy — including AI/agent strategy — into executable programs with clear milestones and measurable outcomes.
Communicate complex technical and AI architecture clearly to both technical and non-technical audiences, using diagrams and visual storytelling where helpful.
Manage vendor and contingent workforce strategies while leading technology research and innovation across AI/agents, cloud, cross-platform app frameworks, and distributed systems to inform long-term platform investments.
Stay ahead of emerging standards (MCP, agent-to-agent protocols, new app frameworks) and bring them into the roadmap where they create real consumer or engineering value.