AI Delivery Lead
Mansfield · US · USD 150,000-175,000 · Remote · Posted Oct 9, 2026
At a glance
- Workplace
- Remote
- Location
- Mansfield · US
- Salary
- USD 150,000-175,000
About the role
- As an AI Delivery Lead, you will help transform how eClinical Solutions Engineering teams plan, build, test, and deliver software by driving adoption of AI-enabled software development practices across the organization.
- You will work closely with Engineering, SQA, Product Management, Architecture, and DevOps to embed AI-assisted development and automation throughout the Software Development Lifecycle (SDLC).
- You will help teams identify opportunities to eliminate manual activities, improve delivery predictability, strengthen automated quality, and demonstrate measurable improvements in engineering productivity and software delivery.
Responsibilities
- Drive adoption and continuous improvement of AI-assisted development and AI-DLC practices across Engineering teams.
- Work directly with Engineering, SQA, Product, Architecture, and DevOps throughout planning, development, testing, and release.
- Partner with teams during backlog refinement and sprint planning to improve story readiness, identify dependencies, and ensure development and automated testing are considered together.
- Identify opportunities to use AI and automation to reduce manual activities across requirements analysis, development, testing, documentation, and delivery.
- Help teams incorporate AI-assisted workflows into their day-to-day engineering practices using company-approved tools.
- Drive stronger integration between software development and test automation, including API and UI automation as part of feature delivery.
- Identify delivery bottlenecks, dependencies, and process gaps and work with teams to resolve them.
- Establish repeatable AI-enabled delivery practices and help scale successful approaches across multiple Engineering teams.
- Define and track meaningful delivery metrics, including cycle time, rework, automation coverage, manual test reduction, quality, and AI adoption.
Requirements
- Experience leading software delivery across cross-functional Engineering, Product, SQA, Architecture, and DevOps teams, including Agile planning, execution, release management, and dependency management.
- Demonstrated experience introducing or scaling AI-assisted development, AI-enabled delivery, or AI-SDLC practices and translating those capabilities into measurable improvements.
- Experience driving Agile and engineering process transformation, including improvements to cycle time, delivery predictability, automation, quality, and team operating models.
- Experience leading complex initiatives across multiple teams and communicating delivery status, risks, dependencies, and measurable outcomes to senior leadership.
- Strong understanding of the Software Development Lifecycle, including requirements, software development, CI/CD, automated testing, release management, and software quality practices.
- Practical understanding of modern AI-assisted software development tools, agents, and workflows, with the ability to identify where AI and automation can safely improve or replace manual processes.
- Strong Agile delivery capabilities, including backlog readiness, refinement, sprint planning, risk and dependency management, and using delivery metrics to identify and remove bottlenecks.
- Ability to operate as a hands-on change and delivery leader, working directly with engineers, SDETs, Product Managers, architects, and DevOps rather than functioning primarily as a project coordinator or Scrum ceremony facilitator.
Preferred qualifications
- Experience introducing AI-assisted development tools such as Cursor, GitHub Copilot, Claude Code, or similar technologies within software engineering organizations.
- Experience with automated software quality practices, including API testing, UI automation, CI/CD, and continuous testing.
- Experience driving software delivery transformation in life sciences, healthcare, regulated SaaS, or other regulated environments.
- Experience developing dashboards and metrics that provide visibility into engineering productivity, quality, delivery flow, and AI adoption.
Skills
- .NET
- Python
- LLMs
- Cursor
- GitHub Copilot
- Claude Code
- CI/CD
