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This role is for one of our clients
We are looking for a hands-on, deeply passionate Agentic AI Engineer who will help us turn cutting-edge Agentic AI and Multi-agent Systems into real-world value by designing, developing, and deploying intelligent agent solutions that run seamlessly on our clients existing infrastructure — while also powering our own internal product offerings.
Key Responsibilities
•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.
Required Qualifications & Experience
•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
Agentic AI, Multi-agent Systems, MCP servers
CI/CD, MLOps, LLM
Job ID: 150545585
Skills:
Ml, Nlp, Python, Evaluation, LLM pipelines, fine-tuning, agentic AI systems, LLM interfaces, memory evaluation, retrieval, prompt engineering
Skills:
Gcp, MLops, Azure, Kubernetes, AWS, Agentic AI, Multi-agent Systems, MCP servers, CI CD, Llm
Skills:
Microservices, Sql, Numpy, Pandas, Rest Apis, Python, LangChain, RAG frameworks, Vector databases, Pinecone, LangGraph, Agentic AI systems, FAISS, Weaviate
Skills:
Databricks, MLops, AWS, Redis, Python, Azure, Gcp, ML pipelines, advanced RAG systems, Agentic AI GenAI systems, MLflow, hybrid retrieval, OpenSearch, grounding, multi-step agent workflows, ML DL model design, vector databases, CI CD, re-ranking, CrewAI, FAISS, LLM orchestration, LangGraph
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