Designs and maintains production-grade MCP servers, backend services, and secure REST APIs using Node.js, TypeScript, Java, and AWS. Responsibilities include serverless development, OAuth 2.0 and API key security, MCP tool and schema design for LLM agents, monitoring, troubleshooting, validation, and failure recovery. The role collaborates across engineering, product, AI, and infrastructure teams to deliver scalable, reliable, and maintainable AI-enabled integrations.
𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀
𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟮𝟬𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟯𝟱𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟮𝟬-𝟯𝟱 𝗟𝗣𝗔)
Experience: 7+ yrs
Location: Remote (India)
Job Type: Full-time
We are looking for an experienced MCP Backend Engineer with strong expertise in Node.js/TypeScript, Java, AWS, API development, and Model Context Protocol (MCP) to build secure, scalable, and production-ready backend integrations.
The ideal candidate will have hands-on experience designing and implementing MCP servers and integrations, with a strong understanding of how LLMs interact with tools and APIs. You will be responsible for developing reliable backend services, exposing secure tools for AI agents, and ensuring integrations meet high standards of performance, security, and maintainability.
Requirements
Key Responsibilities
- Design, develop, and maintain production-grade MCP servers and MCP integrations.
- Build backend services and APIs using Node.js/TypeScript, with integration across Java-based systems where required.
- Design secure and scalable REST APIs using OpenAPI/Swagger specifications and well-defined versioning strategies.
- Develop and deploy serverless backend solutions using AWS Lambda and API Gateway.
- Configure and work with AWS VPC, Secrets Manager, and CloudWatch for secure networking, credential management, monitoring, and observability.
- Implement secure authentication and authorization mechanisms using OAuth 2.0, including client credentials and on-behalf-of flows.
- Design and manage secure API key authentication and credential-handling processes.
- Define MCP tools, schemas, descriptions, and interfaces that enable LLMs and AI agents to reliably use backend capabilities.
- Understand how tool definitions and descriptions influence LLM and agent behaviour, and continuously improve tool usability and reliability.
- Build appropriate validation, error handling, logging, monitoring, and failure-recovery mechanisms for MCP and API integrations.
- Identify and address authentication, authorization, credential exposure, data-access, and other security risks before production deployment.
- Troubleshoot production issues across MCP servers, APIs, AWS services, authentication flows, and integrations.
- Collaborate with engineering, product, AI, and infrastructure teams to translate requirements into scalable technical solutions.
- Contribute to architecture reviews, technical documentation, coding standards, and engineering best practices.
- Continuously improve the reliability, security, scalability, and maintainability of AI-enabled backend systems.
What Makes You a Great Fit
- 7+ years of professional software engineering experience, including strong hands-on experience building production backend systems.
- Direct experience designing and implementing MCP servers, with at least one MCP integration deployed to production or actively used.
- Strong proficiency in Node.js or TypeScript.
- Mandatory familiarity with Java and Java-based backend systems.
- Strong hands-on experience with AWS Lambda, API Gateway, VPC, Secrets Manager, and CloudWatch.
- Solid understanding of REST API design, OpenAPI/Swagger, API versioning, and backend integration patterns.
- Practical experience implementing OAuth 2.0, including client credentials and on-behalf-of flows.
- Experience with API key management and secure credential handling.
- Strong understanding of how LLMs consume tool definitions and how tool descriptions, schemas, and interfaces affect agent behaviour.
- Strong security mindset with a clear understanding of authentication vs. authorization.
- Ability to identify credential exposure, access-control, data-protection, and integration risks early in the development lifecycle.
- Strong debugging, problem-solving, and production troubleshooting skills.
- Experience designing reliable, scalable, observable, and maintainable backend systems.
- Strong understanding of API security, cloud security, logging, monitoring, and secure integration practices.
- Excellent communication and collaboration skills with the ability to work effectively in a remote environment.
- Strong ownership mindset and ability to independently drive backend and AI integration initiatives from design through production.
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