Required Skills: SDLC, Agile, Cursor, GitHub Copilot, AWS, Azure, GCP
Job Description
Required Skills
• Principal-Level Technical Leadership: 15+ years of hands-on experience in the SDLC, with the ability to lead by expertise, guidance, and oversight for senior engineering teams.
• AI-Native Tooling Mastery: Deep, demonstrable proficiency in Claude Code (Required), Cursor, or GitHub Copilot.
• Modern Tech Stack Expertise: Extensive and architect-level experience with modern tech stacks (ie Java Spring Boot, Microservices), modern databases (ie relational, NoSQL) and a modern SPA framework/architecture (ie React).
• Architectural Orchestration: Proven ability to move beyond "syntax production" to "architectural oversight," framing problems for AI with precision and constraints.
• Cloud & DevOps Integration: Practical experience with GitHub, GitHub Actions, code quality tools and Cloud environments (AWS/Azure/GCP) to align AI workflows with CI/CD pipelines.
• Critical Review Mastery: Expert-level capability in modern coding patterns such as TDD (Test Driven Development), Microservice architecture and the ability to audit AI-generated code for "vibe coding" vs. robust, idiomatic engineering.
• OCM Strategy & Implementation: Practical experience with Organizational Change Management concepts; training user communities, building a "Community of Practice" that fosters peer-to-peer learning and cultural buy-in.
Job Duties
• Develop Training Curricula: Architect and deliver comprehensive training program(s) that professionalize Claude Code proficiency by mastering context engineering, agentic lifecycle management, and iterative verification loops to ensure high-performance, cost-efficient AI integration.
• Lead the Developer AI Transformation: Serve as the hands-on trainer and mentor for the developer community, facilitating the shift from manual execution to AI-driven orchestration. Lead through formal training, community-led peer-to-peer sessions and other formats which foster developer engagement in the AI transformation.
• Design Career Migration Paths: Collaborate with the OCM team to develop role-specific journeys that show developers how their daily activities will evolve and flourish in an AI-augmented environment.
• Standardize AI Configuration: Train developers to understand and contribute to the proper use of .claudecode, CLAUDE.md, and skills to bake enterprise standards into the AI’s persistent memory.
• Collaborate with EQE & Governance: Work closely with AI Governance and Security teams to incorporate rules, regulations, and "Dos and Don'ts" into the developer's daily IDE workflow. Help promote and increase adoption of enablement tools and services.
• Legacy Systems Modernization Focus: Tailor training to enhance AI-enabled strategies for analyzing, documenting, and refactoring legacy applications into modern architectures.
• Foster a Community of Practice: Establish and lead "Office Hours," workshops, and community forums to encourage peer-to-peer learning and mitigate institutional anxiety.
• Refine Requirements with AI: Teach developers how to use Claude to enhance User Stories and Acceptance Criteria by injecting codebase-specific context.
• Manage Token Stewardship: Educate teams on disciplined token consumption and managing the "cost of context" for performance efficiency.
Job Requirements
• 15+ Years SDLC Experience: Comprehensive background in Agile methodologies, Design Patterns, and Microservices Architecture.
• 2+ Years AI-Assisted Development: Proven track record using agentic AI tools and code assist tools in real-world, enterprise-level production environments.
• Full Stack Proficiency: Extensive experience with modern tech stacks. Java, Spring Boot, Web APIs, microservices, React a plus.
• Exceptional Communication & "Teacher’s Mindset": Must be a polished presenter capable of speaking to executive, technical and non-technical audiences. Establish credibility with senior-level developers through demonstrable real-world knowledge.
• Polished Change Agent: Must have the emotional intelligence to manage the psychological transition of a large engineering org, moving them from "hands-on-keyboard" execution to an "AI-orchestration" identity without losing institutional morale.
• TDD & Quality Advocacy: A firm believer in "Design-First" approaches; ability to teach developers how to correct AI output and implement automated quality gates.
• Enterprise Savvy: Comfortable navigating restricted environments, governance gates, and security restrictions common in large-scale organizations.
• Critical Thinking: Ability to balance the "Technical ABCs" (the how) with the "Strategic Why," ensuring a resilient and adaptable workforce.