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Senior AI Integration & Platform Engineer

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Senior AI Integration & Platform Engineer

Talent Corner Hr Services

Senior AI Integration & Platform Engineer

Skills

Google Cloud PlatformDockerTypescriptPythonJavaGraphQLAIAWSGitHubKubernetesComplianceJavascriptAzure

18 days ago

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Important information


Contract type:

Permanent

Salary:

₹1,000,000 – ₹2,000,000 / year

Location:

India

Work mode:

Remote

Published on:

5 October 2026

What they need


Senior AI Integration & Platform Engineer

Experience: 8+ Years
Location: Remote PAN India
Preferred Locations: Noida / Pune / Bangalore / Gurgaon / Indore / Ahmedabad / Chennai
Employment Type: Full-Time

Job Overview:

We are looking for a Senior AI Integration & Platform Engineer with 8+ years of experience in software engineering, cloud platforms, application development, and enterprise integrations.

The ideal candidate will have strong hands-on experience with MCP (Model Context Protocol), AI Agents, LLM applications, REST/GraphQL APIs, Microsoft Copilot extensibility, Microsoft Graph, and cloud platforms.

This role will focus on building secure, scalable, and reusable AI integrations, connectors, plugins, and extensions that improve developer productivity and enable AI capabilities across the software development lifecycle.

Key Responsibilities:

  • Design, develop, and maintain AI connectors and integrations using MCP, REST/GraphQL APIs, webhooks, and enterprise platforms.
  • Build reusable AI skills, plugins, connectors, and extensions for platforms such as Microsoft 365 Copilot, GitHub Copilot, and other GenAI platforms.
  • Develop and integrate AI agents and tool/function-calling capabilities into enterprise applications and development workflows.
  • Build LLM-powered applications using prompt engineering, retrieval, and effective context management.
  • Integrate AI capabilities across the software development lifecycle to improve developer productivity, automation, and delivery outcomes.
  • Ensure integrations meet enterprise requirements for security, authentication, governance, compliance, observability, and lifecycle management.
  • Work with cloud platforms such as Azure, AWS, or GCP and containerized environments.
  • Implement secure authentication and authorization using OAuth 2.0, OIDC, and secure credential management practices.
  • Support CI/CD, automated testing, Infrastructure as Code, and production deployment of AI integrations.
  • Create technical documentation and provide enablement, guidance, and support to development teams adopting AI-enabled solutions.
  • Continuously evaluate emerging GenAI, AI agent, MCP, and enterprise AI technologies and identify opportunities for adoption.

Must-Have Skills:

  • MCP (Model Context Protocol)
  • AI Agents / Agentic AI / Tool Calling / Function Calling
  • LLM / Generative AI Application Development
  • REST / GraphQL API Development & Integration
  • Microsoft Graph & Microsoft 365 Copilot Extensibility
  • Python / Java / TypeScript / JavaScript
  • Prompt Engineering, Retrieval, RAG, and Context Management
  • Azure / AWS / GCP
  • Docker / Containers
  • OAuth 2.0 / OIDC
  • CI/CD and Infrastructure as Code
  • Automated Testing, Security, Governance, and Observability

Preferred / Good-to-Have Skills:

  • Hands-on experience with GitHub Copilot
  • Experience building Copilot plugins, connectors, or extensions
  • Experience with enterprise GenAI platforms
  • Experience in developer productivity platforms and software engineering tools
  • Experience with Kubernetes and cloud-native architectures
  • Knowledge of AI governance, compliance, monitoring, and production lifecycle management

AI Expectations:

The candidate should be a regular user of enterprise AI tools such as:

  • GitHub Copilot
  • Microsoft 365 Copilot
  • Other enterprise GenAI platforms

The candidate should be able to demonstrate practical use of AI for coding, documentation, analysis, automation, troubleshooting, and productivity improvement.

Candidate Profile:

  • 8+ years of strong software engineering experience.
  • Strong hands-on development and enterprise integration experience.
  • Proven experience working with GenAI/LLM applications and AI agents.
  • Strong understanding of APIs, cloud platforms, authentication, and secure enterprise integrations.
  • Excellent communication and collaboration skills.
  • Ability to work with development teams, document solutions, and support adoption of AI-enabled platforms.

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