Principal AI Enablement & SDLC Coach

About the role

Our client, a leading organization within the insurance industry, is seeking a Principal AI Enablement & SDLC Coach to lead the next evolution of software engineering through AI-native development practices. This is a unique opportunity for a senior-level technologist who combines deep software engineering expertise with a passion for coaching, organizational transformation, and developer enablement. You will serve as a trusted advisor to engineering teams, helping modernize software delivery by guiding developers from traditional coding workflows toward AI-augmented software orchestration using Claude Code and other emerging AI technologies. The ideal candidate brings principal-level engineering experience, strong communication skills, and the credibility to engage senior developers, architects, engineering leaders, and executives.

Responsibilities

• Lead AI Transformation Across Engineering: Drive adoption of AI-native software development methodologies across engineering teams; coach developers on transitioning from manual execution to AI-assisted orchestration and accelerated software delivery; facilitate formal training sessions, workshops, office hours, and peer-learning communities.
• Develop Enterprise Training Programs: Design and deliver comprehensive learning paths focused on Claude Code, context engineering, agentic workflows, and AI-assisted development patterns; build training materials and enablement resources that improve developer productivity while maintaining quality and governance standards.
• Design Career Evolution Paths: Partner with engineering leadership and stakeholders to define role-specific AI adoption journeys; help developers understand how responsibilities evolve within AI-augmented engineering environments.
• Establish AI Development Standards: Educate teams on enterprise AI configurations, including Claude project structures, persistent context management, and reusable skill frameworks; promote consistent engineering practices and governance-aligned AI usage.
• Partner with Engineering Excellence & AI Governance: Incorporate security, compliance, governance, and organizational policies into day-to-day developer workflows; collaborate with architecture, security, and platform teams to encourage responsible AI adoption.
• Foster Communities of Practice: Build and lead internal communities focused on AI engineering excellence; create forums that encourage collaboration, knowledge sharing, and continuous learning.
• Improve Requirements & SDLC Practices: Teach engineering teams how to leverage AI to refine user stories, acceptance criteria, technical designs, and delivery workflows; advocate for design-first thinking, TDD practices, and automated quality validation.
• Promote Cost-Effective AI Usage: Guide teams on effective context management, prompt engineering strategies, and responsible token consumption; help teams balance productivity gains with platform efficiency and governance requirements.

Requirements

• Technical Leadership: 15+ years of software engineering, architecture, or SDLC leadership experience; proven success influencing senior engineers, architects, and technical leadership teams; strong understanding of enterprise software development practices and engineering transformation initiatives.
• AI-Native Development Expertise: Demonstrated hands-on experience with Claude Code and AI-assisted software development workflows; experience implementing AI solutions across software delivery lifecycles; ability to evaluate and improve AI-generated output through structured review, validation, and testing practices.
• Full Stack Engineering Background: Strong experience with Java, Spring Boot, REST/Web APIs, microservices architecture, modern relational and NoSQL databases, React or other modern SPA frameworks.
• Coaching & Communication: Exceptional presentation, mentoring, and facilitation skills; ability to communicate effectively with executive, technical, and non-technical audiences; experience building training programs, mentoring developers, or leading technical enablement initiatives.
• Organizational Change Management: Experience leading large-scale technology adoption or transformation programs; ability to support cultural change and drive adoption across engineering communities; strong emotional intelligence and stakeholder management capabilities.
• Quality & Engineering Excellence: Strong advocate of Test-Driven Development (TDD), automated testing, and quality-first engineering practices; ability to teach developers how to validate, refine, and productionize AI-generated solutions.
• Enterprise Environment Experience: Experience operating within complex enterprise environments with security, governance, compliance, and regulatory requirements; strong critical thinking and problem-solving skills with the ability to connect technical execution to business outcomes.

Qualifications

• Experience with Kubernetes and Docker.
• Cloud experience in AWS, Azure, and/or GCP environments.
• Experience integrating AI workflows into CI/CD pipelines