AI Expert

JOB OVERVIEW

The AI Champion is a senior technical role responsible for embedding AI/LLM technologies across the full Software Development Life Cycle (SDLC) to significantly improve engineering quality, delivery speed, and developer productivity. This person acts as the bridge between software engineering teams and AI capabilities, ensuring practical, scalable, and safe adoption of AI tools and workflows.

Ideal for individuals with Solution Architect or Technical Lead background, who understand SDLC deeply and are passionate about applying AI to real-world development challenges.

RESPONSIBILITIES

AI Integration Into SDLC

• Identify opportunities to embed AI into each SDLC stage: requirements, design, coding, code review, testing, deployment, monitoring.
• Build and maintain AI-powered accelerators (e.g., code agents, test generators, knowledge assistants).
• Lead PoCs for new AI/LLM tools and evaluate their impact on productivity and quality.
• Standardize best practices for secure and compliant use of AI in engineering.

Developer Productivity & Quality Enhancement

• Introduce AI copilots for coding, debugging, documentation, CI/CD, and testing.
• Design workflows that reduce manual effort: automated test generation, defect prediction, static code analysis enhancement.
• Measure and benchmark productivity improvements using DORA metrics, cycle time, test coverage, defect leakage, etc.

Engineering Enablement & Governance

• Train engineering teams on AI usage, patterns, and safe practices.
• Define guardrails, policies, and evaluation frameworks for AI-based development.
• Collaborate with Platform/DevOps teams to integrate AI into pipelines (CI/CD, quality gates, PR bots).
• Ensure the ethical, secure, and cost-efficient use of AI models.

Collaboration & Stakeholder Management

• Work closely with Product Owners, Engineering Managers, SAs, and DevOps to align AI initiatives with business goals.
• Partner with cloud providers (AWS, Azure, Google, NVIDIA) to leverage their AI offerings.
• Participate in architecture decisions from an AI-first perspective.

REQUIREMENTS

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 5+ years as Solution Architect, Technical Lead, or Senior Software Engineer.
• Deep understanding of SDLC, CI/CD, cloud-native architecture, and enterprise software development.
• Strong foundation in software engineering principles, design patterns, and system architecture.

AI/ML Skills

• Hands-on experience with AI/LLM tools (e.g., GitHub Copilot, Azure OpenAI, HuggingFace, AWS Bedrock, LangChain).
• Understanding of context engineering, RAG, model evaluation, and AI safety basics.
• Ability to prototype simple AI features: agents, automations, workflows.

Soft Skills

• Strong analytical and problem-solving mindset.
• Ability to influence engineers and drive change.
• Good communication and training skills.

Preferred Qualifications

• Experience with MLOps / AIOps / cloud AI services.
• Experience building internal engineering platforms or productivity tools.
• Understanding of security, compliance, and responsible AI principles.
• Experience with microservices, containerization, and DevOps pipelines.