AI SDLC Enablement Lead

Our client is a leading technology and consulting organization focused on delivering cutting‑edge digital solutions, AI‑powered products, and enterprise‑scale transformation programs. They work with global partners to design, build, and operationalize innovative tools and platforms that accelerate business value.

We are looking for an AI SDLC Enablement Lead to transform how engineering teams build software by embedding AI tools directly into the Software Development Lifecycle (SDLC). Your mission is to accelerate delivery, improve quality, and enhance developer experience - all while ensuring proper governance, security, and compliance.

This is a hands‑on technical leadership role spanning engineering excellence, AI integration, change management, and cross‑team enablement.

* Design and implement AI‑augmented SDLC workflows across development, QA, and Dev Ops teams

* Define standard AI usage patterns and best practices for engineering organizations

* Integrate AI tools with Git Hub/Git Lab, Jira/Azure Dev Ops, and CI/CD pipelines

* Establish guardrails for secure code generation, IP protection, and prompt reuse/versioning

* Measure impact using SDLC KPIs such as cycle time, defect leakage, test coverage, and developer productivity

* Partner closely with Security, Legal, and Platform teams to ensure compliant and governed AI usage

* Provide coaching, guidance, and change leadership to drive adoption of AI‑assisted development across engineering teams

* 8+ years of experience in software engineering or Dev Ops

* Hands‑on use of AI coding tools such as Cursor and Git Hub Copilot

* Strong understanding of CI/CD pipelines and modern SDLC methodologies including Agile and Dev Sec Ops

* Deep knowledge of secure coding practices and risks associated with AI‑assisted development

* Proven ability to lead change, coach engineering teams, and enable large‑scale adoption of AI‑enhanced workflows

* Excellent communication skills and ability to collaborate effectively with security, legal, and platform stakeholders

* Experience with AI‑powered QA tooling

* Familiarity with enterprise engineering platforms

* Exposure to AI governance frameworks