AI-Native Developer (AI-Assisted Engineering)

Role Summary

Key Responsibilities

• Use AI tools for coding, testing, documentation, debugging, and optimisation
• Drive AI adoption across end-to-end SDLC (requirements → development → testing → support)
• Act as AI champion – guide, coach, and support team in effective tool usage
• Define and enforce AI engineering best practices and guardrails
• Enable &Client;20% productivity improvement through AI-assisted development
• Monitor quality of AI-generated outputs (code, test cases, documentation)

Core Skills

• Strong development experience in:
  • Java
• Hands-on experience with:
  • GitHub Copilot, Codex, Cursor, Claude Code
• Strong understanding of:
  • Prompt engineering (zero-shot, few-shot, CoT)
  • SDLC/PDLC processes with AI integration

AI & Advanced Capabilities

• Experience with:
  • RAG pipelines (data ingestion, chunking, embeddings, retrieval)
  • Agentic AI systems and multi-agent workflows
  • MCP tools and connectors for enterprise integrations
• Ability to build:
  • Data ingestion pipelines (structured & unstructured)
  • AI-enabled developer workflows integrated with tools like JIRA/Confluence

Key Success Metrics

• &Client;20% improvement in development productivity
• Increased AI adoption across teams
• Improved code quality & reduced defects

Role Focus

• Hands-on + Enablement role (not purely individual contributor)
• Drives AI-led engineering transformation within the team