Position Summary :

The AI Solutions Engineer is a hands-on technical role responsible for designing, developing, and deploying advanced AI agents and intelligent applications, with a strong focus on Model Context Protocol (MCP)driven architectures and Microsoft Copilot extensibility.

This role requires deep expertise in building robust, stateful AI systems using Python, LangChain, and LangGraph, and in developing scalable agent-based solutions that integrate seamlessly with enterprise platforms.

The ideal candidate will play a critical role in designing and implementing MCP-enabled services, developing custom agents and plugins for Microsoft Copilot, and optimizing agent performance, orchestration, and contextual awareness.

This includes building and managing MCP servers, enabling secure tool and data access for AI agents, and ensuring scalable and reliable deployment using modern infrastructure technologies such as Docker and NGINX.

Strong collaboration, problem-solving, and communication skills are essential, as this role partners closely with cross-functional teams to deliver intelligent, enterprise-grade AI solutions.

Given the rapid evolution of AI technologies, frameworks, and enterprise platforms, this role requires a continuous learning mindset.

Responsibilities, tools, and required skills are expected to evolve over time, and the candidate must be adaptable and proactive in adopting emerging AI capabilities, including advancements in MCP, agent frameworks, and Microsoft Copilot ecosystems.

Key Responsibilities :

- Design, build, and optimize advanced, stateful AI agents and multi-agent applications using Python, LangChain, and LangGraph,Copilot

- Develop, deploy, and manage Model Context Protocol (MCP) integrations, enabling secure and seamless communication between AI agents, enterprise systems, and external services including databases, APIs, file systems, and object storage

- Build and extend Microsoft Copilot (M365 Copilot / Copilot Studio) solutions by developing custom agents, plugins, connectors, and orchestration workflows

- Architect and implement context-aware, tool-using agents leveraging MCP for dynamic context sharing, memory, and intelligent decision-making

- Utilize Docker and Docker Compose for containerization and orchestration of AI agents, MCP servers, and supporting services to ensure scalable and reproducible deployments

- Configure and manage web servers (e.g., NGINX or equivalent) to optimize routing, performance, and secure access to AI services and agent endpoints

- Collaborate with frontend and application teams to integrate AI agents and Copilot-driven capabilities into user-facing applications and enterprise workflows

- Implement testing, validation, and monitoring frameworks to ensure reliability, accuracy, performance, and security of AI agents and MCP-enabled systems

- Troubleshoot and optimize AI applications and distributed agent systems for scalability, latency, and operational efficiency

- Work closely with cross-functional teams (engineering, product, business stakeholders) to translate requirements into scalable, intelligent AI solutions, maintaining clear technical documentation

- Demonstrate adaptability and a continuous learning mindset as AI technologies, MCP standards, and Microsoft Copilot capabilities rapidly evolve, ensuring solutions remain modern, scalable, and aligned with emerging best practices

Required Skills & Qualifications :

- Strong proficiency in Python and related frameworks for AI/ML and backend development (e.g., FastAPI, Pandas, async programming patterns)

- Hands-on experience with LangChain and LangGraph for building LLM-powered applications, agent workflows, and multi-agent orchestration

- Demonstrated experience designing and implementing AI agents and intelligent workflows, including tool integration, memory management, and context-aware reasoning

- Strong understanding and practical experience with Model Context Protocol (MCP), including building and integrating MCP clients, servers, and MCP-compliant services

- Experience developing and extending Microsoft Copilot (M365 Copilot / Copilot Studio) through custom agents, plugins, connectors, and orchestration logic

- Solid experience with Docker and Docker Compose for containerization and deployment of AI agents and MCP services; familiarity with CI/CD pipelines and Kubernetes fundamentals is a plus

- Experience configuring and managing web servers (e.g., NGINX or equivalent) for reverse proxy, load balancing, and secure communication (SSL/TLS)

- Strong understanding of integrating AI systems with external services (databases, APIs, file systems, object storage) in a secure and scalable manner

- Strong analytical, problem-solving, and troubleshooting skills for complex, distributed AI and agent-based systems

- Demonstrated ability and willingness to continuously learn and adapt to rapid advancements in AI technologies, MCP standards, agent frameworks, and Microsoft Copilot capabilities, ensuring solutions remain modern, scalable, and aligned with industry best practices

Education :

Bachelors degree in Computer Science, Engineering, or a related technical field (preferred)