Here is an exciting Opportunity - AI Engineer | Capgemini

Capgemini; Hyderabad; On-site; INR 1,800,000 - 2,600,000; Full time

Job summary

Capgemini is seeking an AI Engineer to design and evolve AI agents for software architecture, code review, testing, and modernization. You will define skills, prompts, and orchestration patterns to create reusable AI capabilities across the platform.

The role focuses on building multi-step workflows, improving reasoning and context management, and integrating with GitHub, Azure DevOps, Jira, and other developer tools, while enforcing governance and security controls.

Qualifications

• Hands-on experience with LLMs, AI agents, RAG architectures and prompt engineering.
• Experience building agent-based systems, autonomous workflows and copilots.
• Strong TypeScript/Node.js development and API integration skills.
• Familiarity with VS Code extensions and developer tooling ecosystems.
• Practical use of AI developer tools like Copilot, Claude Code, Cursor, Windsurf or Continue.dev.

Responsibilities

• Design, build, and evolve AI agents for software architecture, code review, testing, modernization, documentation generation, and release management.
• Define and implement skills, prompts, templates, orchestration patterns, and reusable AI capabilities across the platform.
• Build multi-step workflows coordinating agents, tools, approvals, governance, and external systems.
• Improve reasoning quality, context management, retrieval mechanisms, and response accuracy.
• Evaluate and integrate leading AI technologies including GitHub Copilot, Claude Code, OpenAI models, MCP servers, and emerging agentic frameworks.
• Develop enterprise-grade prompt engineering, context engineering, and grounding strategies for software engineering use cases.
• Build integrations with GitHub Enterprise, Azure DevOps, Jira, knowledge repositories, and developer platforms.
• Design governance-aware execution models enforcing policies, security controls, and approval gates.
• Continuously benchmark tool/platform capabilities and identify improvement opportunities.
• Drive innovation around autonomous software development and AI-assisted modernization.

Skills

AI Engineering

Agentic Frameworks

TypeScript Ecosystem

VS Code Extension Knowledge

AI Developer Tools

Software Engineering

Integration Development

Problem Solving

Testing Skills

Tools

GitHub Copilot

Claude Code

Cursor

Windsurf

Continue.dev

Job description

Key Responsibilities

• Design, build, and evolve AI agents for software architecture, code review, testing, modernization, documentation generation, and release management.
• Define and implement skills, prompts, templates, orchestration patterns, and reusable AI capabilities across the platform.
• Build multi-step workflows that coordinate agents, tools, human approvals, governance policies, and external systems.
• Improve reasoning quality, context management, retrieval mechanisms, and response accuracy across AI-powered workflows.
• Evaluate and integrate leading AI technologies including GitHub Copilot, Claude Code, OpenAI models, MCP servers, and emerging agentic frameworks.
• Develop enterprise-grade prompt engineering, context engineering, and grounding strategies for software engineering use cases.
• Build integrations between AI agents and developer ecosystems including GitHub Enterprise, Azure DevOps, Jira, knowledge repositories, and developer platforms.
• Design governance-aware execution models that enforce organizational policies, security controls, auditability requirements, and approval gates.
• Continuously benchmark the tool/platform capabilities and identify improvement opportunities.
• Drive innovation around autonomous software development, Spec Driven Development, AI-assisted modernization, and engineering productivity acceleration.

Mandatory Skills

AI Engineering: Hands-on experience working with LLMs, AI agents, RAG architectures, prompt engineering, context engineering, tool calling, MCP, memory systems, and agent orchestration.

Agentic Frameworks: Experience building or customizing agent-based systems, autonomous workflows, multi-agent solutions, or AI copilots.

TypeScript Ecosystem: Strong development skills using TypeScript, Node.js, npm, modern JavaScript frameworks, and API integrations.

VS Code Extension Knowledge: Working knowledge of VS Code extensions, Chat Participants, Commands, WebViews, extension APIs, async programming, promise handling and developer tooling ecosystems

AI Developer Tools: Practical experience using GitHub Copilot, Claude Code, Cursor, Windsurf, Continue.dev, or similar AI-assisted engineering platforms.

Software Engineering: Strong understanding of software architecture, design patterns, code quality, testing, DevOps, CI/CD, secure SDLC, and modernization initiatives.

Integration Development: Experience integrating applications with GitHub, Azure DevOps, Jira, REST APIs, MCP Servers, databases, and enterprise platforms.

Problem Solving: Ability to translate complex SDLC challenges into reusable workflows, agents, AI capabilities, and platform services.

Testing Skills: Familiarity with unit testing frameworks like Jest, Mocha, etc.