Position Summary
The
AI Enablement Specialist will drive the adoption and optimization of AI-assisted practices across the Software Development Lifecycle (SDLC). This role focuses on embedding AI technologies into design, development, testing, and deployment processes to accelerate delivery, enhance quality, and foster innovation. Acting as a cross-functional technical lead, the specialist will collaborate with development PODs, architects, product owners, and QA teams to institutionalize AI-driven efficiencies across engineering practices.
Key Objectives
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Accelerate the SDLC: Integrate AI-driven automation into design, development, and testing workflows to shorten delivery cycles.
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Increase Developer Productivity: Eliminate repetitive, high-effort tasks through AI tools for code scaffolding, documentation, and design automation.
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Enhance Quality & Consistency: Improve code quality, testing coverage, and overall reliability using AI-powered review and test tools.
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Foster Continuous Innovation: Encourage experimentation with emerging AI tools and frameworks to modernize the engineering ecosystem.
Scope Of Work & Responsibilities
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Workflow Assessment: Analyze current SDLC processes to identify bottlenecks and prioritize AI intervention opportunities across PODs.
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Tool Evaluation & Integration
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Evaluate And Integrate AI Tools For
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> UI/UX design automation (e.g., Figma plugins, design-to-code tools).
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Code generation (e.g., GitHub Copilot, Azure OpenAI, ChatGPT).
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> API documentation and scaffolding (e.g., Swagger/OpenAPI with AI assistants).
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Automated test generation, coverage analysis, and intelligent refactoring.
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Pilot tools within sprints, measure impact, and refine based on feedback.
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Custom AI Solutions: Develop lightweight AI/ML models or automation scripts where off-the-shelf tools cannot fully address workflow needs.
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Governance & Best Practices: Establish AI usage standards and guardrails for code quality, security, and responsible AI adoption.
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Enablement & Training: Lead workshops on prompt engineering, code assistant optimization, and AI tool workflows. Build and sustain an internal AI champions network.
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Continuous Improvement: Collect usage metrics (e.g., productivity, cycle time, code quality) and drive iterative enhancements across sprints.
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Collaboration & Reporting
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Work closely with engineering, architecture, and security teams to ensure alignment and compliance.
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Report progress and outcomes to program steering committees or senior leadership.
Required Skills & Experience
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Experience
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> 10+ years in software engineering, architecture, or DevEx/AI+MLOps roles.
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Proven success deploying AI tooling at scale across SDLC workflows (e.g., pilots, org-wide rollouts).
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Strong background in delivering enterprise-grade web and API solutions using .NET, Java, Node.js, or Python.
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AI And Automation Expertise
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Hands-on experience with GitHub Copilot, Azure OpenAI, ChatGPT, or similar AI assistants for code, tests, and documentation.
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Ability to design prompt engineering templates, define repository-specific rules, and operationalize AI code-review workflows.
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Familiarity with design-to-code automation and API contract generation tools.
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Development Tooling Knowledge
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> IDEs: VS Code, JetBrains, GitHub Copilot/Models
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> CI/CD: GitHub Actions, Azure DevOps Pipelines (multi-stage, gated releases)
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> UI/UX: Figma, Storybook, design tokens, plugins
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> APIs: OpenAPI/Swagger, Stoplight, Postman
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Testing: Jest, Cypress, Playwright, Pact
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Cloud/IaC: Azure (App Services, AKS, Key Vault, Monitor), Terraform/Bicep, Docker/Kubernetes
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Technical Mastery
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Deep understanding of SDLC, branching, code review, testing (unit, integration, e2e), and CI/CD processes.
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Cloud-native application design and platform configuration (Azure preferred).
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Soft Skills
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Strong stakeholder influence and cross-functional communication.
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Proven capability to lead workshops, demos, and training programs.
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Analytical and experimental mindset comfort with ambiguity, data-driven decisions, and iterative problem-solving.
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Risk awareness and mitigation planning for secure and compliant AI adoption.
Preferred Qualifications & Certifications
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Bachelor's or Master's degree in Computer Science, Software Engineering, or related field.
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Certifications Preferred (any Of)
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Microsoft Certified: Azure AI Engineer / DevOps Engineer Expert
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> GitHub Copilot Enterprise Enablement Specialist (or equivalent)
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Certified Kubernetes Administrator (CKA)
- p]:pt-0 [&>p]:mb-2 [&>p]:my-0> Prompt Engineering / Generative AI Certification (OpenAI, DeepLearning.AI, or equivalent)
Skills: ci/cd,microsoft certified,github,azure,node.js,azure cloud,mlops,azure open ai,api,python,.net,ui/ux design,ai,java
