Senior AI Engineer

• Design, build, and optimize Multi-agent Systems and Agentic AI architectures that deliver measurable business outcomes.
• Develop agentic workflows to automate complex, multi-step processes across domains (finance, operations, customer support, data engineering, etc.).
• Architect and implement production-grade Agentic AI services that clients can deploy on their own infrastructure (on-prem, private cloud, or hybrid).
• Lead the deployment of MCP servers and related agent orchestration layers on multiple cloud and data platforms, with deep expertise in Azure and Databricks.
• Integrate agents with existing enterprise systems, data lakes, APIs, and security frameworks without requiring clients to rip-and-replace their stack.
• Continuously evaluate and integrate the latest Agentic AI frameworks, memory systems, tool-use patterns, and reasoning engines (ReAct, Plan-and-Execute, multi-agent collaboration protocols, etc.).
• Collaborate with client engineering teams to co-create and productionize custom agents that operate securely within their environments.

• Proven track record of developing agentic workflows that automate end-to-end business processes.
• Strong experience with deployment of MCP servers and agent orchestration platforms.
• Experience deploying Agentic AI solutions across multiple platforms (Azure, AWS, GCP, on-prem, Kubernetes) and making them work reliably in client-controlled environments.
• Solid understanding of MLOps, CI/CD for AI, monitoring

Must-have skills

Agentic AI, Multi-agent Systems, MCP servers

Good-to-have skills

CI/CD, MLOps, LLM