Lead AI Architect- Remote- Full Time

Role: Lead AI Architect

Location: 100% Remote

Job Type:  Full Time

Responsibilities:

• Agentic SDLC Design — Architect and implement end-to-end AI-augmented SDLC pipelines using autonomous agents and sub-agents that handle tasks spanning requirements analysis, code generation, review, testing, and deployment.
• GitHub Copilot Agent Engineering — Design, configure, and extend GitHub Copilot agents, custom skills, and agent instructions to automate repetitive engineering tasks, enforce coding standards, and accelerate developer productivity across teams.
• Multi-Agent Orchestration — Build and manage multi-agent systems with clearly defined agent roles, skills, and handoff protocols — including planner agents, coder agents, reviewer agents, and test agents — ensuring reliable and deterministic outcomes.
• AI-Driven Code Quality & Governance — Integrate AI agents with static analysis, linting, and security scanning tools (e.g., SonarQube, CodeRabbit) to enforce quality gates, detect vulnerabilities, and provide real-time feedback within CI/CD pipelines.
• Automated Testing with AI Agents — Leverage AI agents to auto-generate unit tests, integration tests, BDD scenarios (Gherkin/Cucumber), and test data — continuously improving test coverage with minimal manual effort.
• Prompt Engineering & Skill Development — Design reusable, parameterised prompts and agent skills tailored to domain-specific engineering contexts (e.g., banking APIs, microservices, cloud-native patterns), enabling consistent and context-aware code generation.
• AI-Assisted Architecture & Design — Utilise AI agents in the design phase to generate architecture diagrams, ADRs (Architecture Decision Records), API contracts, and design documentation aligned with organisational standards.
• Engineering Best Practices & Standards — Define and enforce AI-assisted development standards including prompt governance, agent observability, output validation, hallucination mitigation, and human-in-the-loop checkpoints for critical workflows.
• Platform Engineering Integration — Embed agentic AI capabilities into internal developer platforms (IDPs), golden paths, and self-service toolchains — enabling teams to consume AI-powered workflows as reusable platform services.
• Continuous Learning & Innovation — Stay at the forefront of agentic AI frameworks (LangGraph, AutoGen, CrewAI, Copilot Extensions), evaluate emerging tools, run proof-of-concepts, and drive adoption of AI engineering innovations across the engineering community.

Skills & Experience:

• Hands-on experience with GitHub Copilot, Copilot Chat, and Copilot Extensions/Agents
• Proficiency in building multi-agent systems using frameworks such as LangGraph, AutoGen, or CrewAI
• Strong software engineering background across at least one major stack (Java/Spring, Python, Node.js)
• Familiarity with CI/CD pipelines, DevSecOps tooling, and quality engineering
• Experience with prompt engineering, RAG patterns, and LLM-based tooling
• Understanding of SDLC governance, testing standards, and code quality practices