รber diese Lead Engineer Stelle bei Weekday AI
๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ฎ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ฏ๐ฑ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ฎ๐ฌ-๐ฏ๐ฑ ๐๐ฃ๐)
Experience: 7+ yrs
Location: Remote (India)
Job Type: Full-time
We are looking for an experiencedย Senior Backend Engineerย with strong expertise inย Node.js/TypeScript, Java, AWS, APIs, and Model Context Protocol (MCP)ย to build production-grade backend systems and AI-powered integrations.
The role focuses on designing and implementingย MCP servers and tool integrationsย that enable Large Language Models (LLMs) and AI agents to securely interact with enterprise systems, APIs, and business applications. The ideal candidate will combine strong backend engineering fundamentals with practical experience building MCP integrations and a deep understanding of API security, authentication, authorization, and cloud infrastructure.
You will be responsible for developing reliable, scalable, and secure services that bridge AI agents with external tools and data sources.
Requirements
Key Responsibilities
- Design, develop, and maintain scalableย backend services and MCP serversย for AI-powered applications.
- Build and deploy production-readyย MCP integrationsย that enable LLMs and AI agents to interact with external tools and systems.
- Define clear and reliable MCP tool schemas, descriptions, parameters, validation rules, and response structures.
- Design RESTful APIs following established API design principles andย OpenAPI/Swagger specifications.
- Implement API versioning strategies that support backward compatibility and safe evolution of integrations.
- Develop cloud-native services usingย AWS Lambda and API Gateway.
- Configure and manage AWS networking components includingย VPCs, security boundaries, and service connectivity.
- Secure application credentials and sensitive configuration usingย AWS Secrets Manager.
- Implement monitoring, logging, alerting, and operational visibility usingย CloudWatchย and related AWS services.
- Implement secure authentication and authorization mechanisms usingย OAuth 2.0, including client credentials and on-behalf-of flows.
- Design and manage secure API key authentication and credential management processes.
- Apply strong security practices across APIs, MCP servers, cloud infrastructure, and integrations.
- Ensure credentials, tokens, secrets, and sensitive data are appropriately protected throughout the application lifecycle.
- Collaborate with product and engineering teams to understand integration requirements and translate them into technical solutions.
- Troubleshoot production issues, investigate integration failures, and perform root-cause analysis.
- Write clean, testable, maintainable, and production-ready code.
- Develop unit, integration, and API tests to ensure reliability and security.
- Contribute to CI/CD pipelines, deployment automation, documentation, and engineering standards.
- Monitor system performance and reliability and identify opportunities for optimization.
- Stay current withย MCP, LLM tooling, AI agent architectures, cloud technologies, API security, and emerging AI integration patterns.
What Makes You a Great Fit
- 7+ years of software engineering experienceย building and operating production backend systems.
- Direct hands-on experience designing and implementingย MCP servers, with at least one MCP integration shipped to production or active users.
- Strong proficiency inย Node.js and/or TypeScript.
- Mandatory familiarity with Javaย and the ability to work effectively with Java-based systems and integrations.
- Strong experience withย AWS Lambda, API Gateway, VPC, Secrets Manager, and CloudWatch.
- Strong understanding of REST API design, API architecture, andย OpenAPI/Swaggerย specifications.
- Experience implementing API versioning and maintaining backward-compatible integrations.
- Hands-on experience withย OAuth 2.0, including client credentials and on-behalf-of flows.
- Strong understanding of API key management and secure credential handling.
- Clear understanding of howย LLMs consume tool definitionsย and how tool descriptions, schemas, and interface design influence agent behaviour.
- Strong understanding of MCP concepts, AI tool calling, agent integrations, and external system connectivity.
- Strong security mindset with practical knowledge ofย authentication vs. authorization, secrets management, credential exposure, and secure API design.
- Experience building reliable distributed backend services and production integrations.
- Strong debugging, troubleshooting, testing, and root-cause analysis skills.
- Familiarity with Git, CI/CD, automated testing, and modern software development practices.
- Strong communication and collaboration skills with technical and non-technical stakeholders.
- Ability to independently own complex backend and AI integration initiatives from design through production.