Lead Director - Software Engineering

CVS Health

Confirmed live today High trust

Closes in 3 days Hybrid

Quick summary

Work type: Hybrid
Location: Wellesley, MAGeorgiaVermontTexasMinnesotaMichiganCaliforniaMaineNew YorkDistrict of ColumbiaNew JerseyConnecticutNevadaRhode IslandLouisianaTennesseeOhioWest VirginiaMassachusettsMarylandSouth CarolinaUtahArizonaVirginiaIllinoisNorth CarolinaColoradoFloridaPennsylvaniaNew HampshireDelaware
Salary: $144,200–$288,400 / yr
Employment: Full-time
Posted: 32 days ago
Freshness: Confirmed live today
Closes: Oct 30, 2026 (soon)
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $214k

This role $216k

$125k $306k

below market most similar roles pay here above market

This role pays more than 60% of similar roles. Most pay $185,500–$243,500 — the blue band above. At the midpoint, this role pays about $216k versus about $214k for comparable roles.

Based on 240 similar postings.

Employer

About CVS Health

CVS Health is a leading American healthcare company operating retail pharmacies, pharmacy benefit management services, and a health insurance segment through Aetna, one of the nation''s largest health insurers. Industry: Healthcare & Pharmacy

CVS Health currently has 119 open roles on FindRole.

Listed pay typically runs $106,605–$260,590 across 115 roles with salary data.

Most-posted roles

View all roles at CVS Health

At a glance

TL;DR · Lead Director - Software Engineering

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The Lead Director - Software Engineering will lead a multi-team engineering organization of 50 to 150+ engineers to drive technical strategy and architectural standards. The role involves defining engineering excellence benchmarks, owning delivery outcomes, and partnering with executive leaders to translate business strategy into engineering bets. Key responsibilities include embedding LLMs, generative AI, agentic workflows, and ML-powered automation into production-grade engineering lifecycles. The successful candidate must possess a deep technical foundation in distributed systems, cloud-native architectures, and modern backend engineering. Required skills include experience with model deployment pipelines, vector databases, RAG architectures, and LLM orchestration. The role specifically addresses the technical challenges of migrating monoliths to microservices and modernizing legacy platforms within highly regulated healthcare environments involving HIPAA and CMS compliance.

Skills

LLMs Generative AI Agentic Workflows Machine Learning RAG Vector Databases Distributed Systems Cloud-Native Architecture Microservices Model Deployment Pipelines Inference Optimization Platform Engineering HIPAA CMS Compliance

What you'll do

Drive technical strategy and architectural standards across a multi-team engineering organization of 50–150+ engineers.
Embed LLMs, generative AI, and ML-powered automation into production-grade engineering lifecycles.
Own delivery outcomes and hold engineering teams accountable for shipping high-quality software at velocity.
Partner with executive leaders to translate business strategies into precise engineering bets and investments.
Act as the technical voice to identify architectural debt and advocate for necessary engineering resources.
Manage the deployment of production AI systems including RAG architectures, vector databases, and inference optimization.
Lead the migration of legacy monoliths to modern microservices and cloud-native architectures.

What we're looking for

10+ years of progressive software engineering experience.
5+ years of experience leading large-scale engineering organizations.
Deep technical foundation in distributed systems, cloud-native architectures, and modern backend engineering at scale.
Proven experience deploying production AI systems including model deployment pipelines, vector databases, RAG architectures, and LLM orchestration.
Track record of migrating monoliths to microservices and modernizing legacy platforms.
Bachelor's degree in Computer Science, Software Engineering, Mathematics, or a related technical discipline, or equivalent demonstrated engineering depth.
Healthcare or highly regulated domain experience (preferred).
Master's degree in Computer Science, AI, Machine Learning, Data Science, or a related quantitative field (preferred).

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