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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - **Company:** Stratedge It Consulting Inc - **Location:** Bellevue, WA, United States - **Experience:** Experienced - **Salary:** $150,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Cloud Computing, Cloud Engineering, Communications Protocols, Databases, Information Engineering, DevOps, Distributed Systems, Memory Management, Machine Learning, Software Deployment, Workflow Management Systems, Enterprise Software Applications, Cloud Platform System, Large Language Models, Multi-Agent Systems, Generative AI, AI Platforms, Information Technology, Virtual Agents, Restful APIs, Network Server, Microservices - **Published:** August 8, 2026 - **Apply:** https://www.dice.com/job-detail/a56bbb19-c316-49c7-b44b-ba813cca2354 ## About the Role Experience: 15+ Years of Overall IT Experience Experience Requirements 15+ years of overall IT experience. 3+ years of AI/ML experience, OR 6+ years of Data Engineering experience. Strong hands-on experience with Agentic AI, MCP servers, multi-agent systems, and enterprise AI integrations., 15+ years of overall IT experience. 3+ years of AI/ML experience or 6+ years of Data Engineering experience. Strong hands-on experience developing MCP servers and MCP tool integrations. Experience designing and implementing Agentic AI architectures. Hands-on experience with multiple Agentic AI frameworks, including: LangChain LangGraph AutoGen CrewAI Semantic Kernel Azure Agentic Framework Strong experience with multi-agent workflow design. Understanding and implementation experience with A2A communication protocols. Experience with agent orchestration, tool use, memory management, context management, and dynamic task routing. Strong understanding of LLMs, APIs, enterprise data sources, and AI application architectures. Experience building scalable and production-ready AI platform components. Preferred Qualifications Experience developing enterprise-scale Generative AI and LLM applications. Experience with RAG, vector databases, embeddings, and knowledge retrieval. Experience integrating AI agents with enterprise applications and APIs. Knowledge of AI security, governance, observability, and responsible AI. Experience deploying AI/ML solutions in Microsoft Azure or other cloud environments. Strong understanding of microservices, distributed systems, REST APIs, and cloud-native architectures. Excellent problem-solving, communication, collaboration, and technical design skills. Education Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, Information Technology, or a related field preferred. ## Description Wipro is seeking a highly experienced AI Engineer to design and develop enterprise-grade Agentic AI solutions, Model Context Protocol (MCP) servers, multi-agent workflows, and AI platform tooling. The ideal candidate will have hands-on experience with MCP server development, tool integrations, Agent-to-Agent (A2A) communication, multi-agent orchestration, and modern Agentic AI frameworks including LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, and Azure Agentic Framework. This role will focus on building reusable, production-ready AI components that enable LLM agents to securely access enterprise APIs, data sources, and services while supporting scalable, observable, and governed agent execution. Key Responsibilities Design and develop Model Context Protocol (MCP) servers and enterprise tool integrations. Build reusable, production-grade tools that expose enterprise APIs, data sources, and services to LLM agents. Enable real-time context retrieval and secure action execution through MCP-based integrations. Design and implement Agent-to-Agent (A2A) communication protocols for enterprise multi-agent systems. Architect multi-agent workflows where specialized agents can collaborate, delegate tasks, exchange information, and share context. Build and manage Agentic AI solutions using LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel, and Azure Agentic Framework. Implement agent orchestration, tool calling, memory management, context handling, and dynamic task routing. Design reusable agent components, tools, workflows, and platform capabilities for enterprise AI applications. Own the agentic platform tooling layer, including agent lifecycle management and reusable AI services. Ensure agent execution is reliable, scalable, observable, secure, and governed across the AI platform. Integrate AI agents with enterprise applications, APIs, databases, cloud platforms, and external services. Collaborate with AI/ML engineers, data engineers, software developers, architects, DevOps teams, and business stakeholders. 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