Required Qualifications

• 5+ years of experience in software engineering, API integration, data engineering, or enterprise application integration
• Hands-on experience with Generative AI / LLM-based applications
• Experience building APIs, connectors, microservices, or enterprise integration layers
• Exposure to Agentic AI, tool-calling, workflow automation, or AI orchestration frameworks
• Bachelor’s or Master’s degree in a relevant field

Role & Responsibilities

• Design, build, and maintain MCP servers exposing enterprise tools, data, and APIs to AI agents
• Develop reusable MCP connectors/adapters for internal and external systems
• Implement MCP-based access to:
• Databases and data platforms
• REST / GraphQL APIs
• Document repositories
• Workflow systems
• Enterprise applications
• Ensure MCP servers are modular, reusable, secure, and observable
• Integrate MCP-enabled tools with LLM applications, copilots, and autonomous agents
• Implement tool invocation patterns for single-agent and multi-agent workflows
• Build integrations between Agentic AI platforms and enterprise systems including:
• ServiceNow, Jira, Confluence
• SharePoint, Teams, Outlook
• Databricks, Snowflake, Synapse
• SQL / NoSQL databases
• CRM, ERP, insurance platforms
• Internal APIs and microservices
• Collaborate with application, data, cloud, and cybersecurity teams to onboard enterprise tools into MCP-based agent ecosystems

Key Role Focus

• Design and implement MCP servers exposing enterprise tools (e.g., Rally, ServiceNow, Confluence, SharePoint, GitHub, Jenkins, Snowflake)
• Define tool schemas, resource URIs, and prompt templates following MCP spec
• Implement authentication patterns (OAuth2, SSO, AWS IAM, service principals) and per-tenant authorization
• Build connectors/adapters to normalize enterprise API quirks (pagination, rate limits, eventual consistency)
• Instrument MCP servers with logging, tracing, metrics, and audit trails for compliance
• Partner with Architect on MCP tool catalog, naming conventions, and versioning strategy
• Triage and resolve agent misuse of tools; improve schemas, descriptions, and error responses
• Deep understanding of MCP specification (resources, tools, prompts, transports — HTTP/SSE)
• Strong API integration background: REST, webhooks, OAuth2/OIDC
• Proficiency in Python and/or TypeScript; familiarity with MCP SDKs
• Knowledge of enterprise integration patterns (retries, circuit breakers, backoff, dead-letter queues)
• Security expertise: secrets vaulting (AWS Secrets Manager / HashiCorp Vault), least-privilege scoping

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