This role is responsible for designing and owning the Model Context Protocol (MCP) architecture that connects LLMs with critical business systems. The ideal candidate will have deep expertise in systems integration, API architecture, and AI platform engineering. The position requires building scalable, secure, and production-ready MCP servers that enable agentic AI workflows across enterprise applications.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a MCP AI Architect based in India.
This role sits at the center of an enterprise-grade AI integration ecosystem, where you will design and own the Model Context Protocol (MCP) architecture that connects LLMs with critical business systems. You will be responsible for building scalable, secure, and production-ready MCP servers that enable agentic AI workflows across enterprise applications. The position requires deep expertise in systems integration, API architecture, and AI platform engineering, with a strong focus on security, governance, and compliance. You will collaborate across technical and business teams to define how AI agents interact with enterprise data and tools. The environment is highly innovative, fast-evolving, and focused on transforming complex organizations into AI-powered enterprises. This is a high-impact role where architectural decisions directly shape the future of internal AI ecosystems and copilots.
Accountabilities
- Design and own the end-to-end MCP server ecosystem, ensuring scalable integration between LLMs and enterprise applications across domains such as healthcare, biotech, and business operations.
- Build and maintain production-grade MCP servers using TypeScript and Python, including secure authentication frameworks such as OAuth 2.0, RBAC, and audit logging.
- Define tool schemas, versioning strategies, and agent orchestration patterns to ensure consistency and reliability across AI systems.
- Integrate MCP layers with enterprise systems such as SAP, Salesforce, D365, Jira, Smartsheet, and Microsoft Graph API based on evolving business needs.
- Architect AI tool invocation models, role-based access controls, and governance frameworks for AI agents and internal copilots.
- Ensure alignment with enterprise security architecture standards and regulatory frameworks including healthcare and AI compliance requirements.
- Maintain MCP registries, documentation, and enablement frameworks while mentoring engineering teams on best practices for agentic AI systems.
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- Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or related field (IIT background mandatory as per role requirements).
- 8+ years of software engineering experience focused on API design, distributed systems, integration platforms, or AI infrastructure.
- 3+ years of hands-on experience building MCP servers or equivalent frameworks such as LangChain, OpenAI Function Calling, or agent-based systems.
- Strong expertise in TypeScript and Python, with deep understanding of REST/GraphQL APIs and Node.js asynchronous architecture.
- Proven experience integrating LLMs (e.g., Claude, GPT-4) into enterprise workflows using RAG or agentic system design.
- Strong knowledge of OAuth 2.0, OIDC, JWT, Azure AD, and enterprise authentication/authorization models.
- Familiarity with regulated environments such as healthcare or life sciences, and awareness of compliance frameworks like GDPR, ISO 27001, or EU AI Act.
- Strong system design, communication, and cross-functional collaboration skills in complex enterprise environments.
- Competitive compensation aligned with senior AI architecture expertise
- Fully remote work model within India
- Opportunity to design cutting-edge MCP and agentic AI systems at enterprise scale
- High-impact role influencing AI architecture across regulated industries
- Exposure to advanced LLM ecosystems, enterprise integrations, and multi-agent frameworks
- Continuous learning environment focused on AI innovation and system design
- Collaborative, engineering-driven culture with strong emphasis on ownership and autonomy
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We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
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