Agentic AI Solution Architect

1 day ago

Hyderabad, Telangana, India Swift Strategic Solutions Inc Full time ₹ 20,00,000 - ₹ 25,00,000 per year

Our technology services client is seeking multiple
Agentic AI Solution Architect
to join their team on a contract basis. These positions offer a strong potential for conversion to full-time employment upon completion of the initial contract period. Below are further details about the role:

Role: Agentic AI Solution Architect

Experience: 15+ Years

Location: PAN India

Notice Period: Immediate- 15 Days

Mandatory Skills: Agentic AI, Azure Architecture, ADF, Structured and Unstructured Field processing, LLM, Python

Job Description:

Architectural Leadership:

  • Own the end-to-end architecture and technical design for the agentic chatbot and its supporting systems within Azure.
  • This includes all components of the retrieval-augmented generation (RAG) pipeline, multi-agent orchestration, and integration layers.

Solution Design:

  • Create detailed architectural blueprints for a system capable of handling over 200,000 enterprise documents.
  • This involves defining the data flow, selecting appropriate Azure services, and designing for scalability, performance, and cost-efficiency.

Data Strategy:

  • Formulate the strategy for ingesting, processing, and indexing large-scale document repositories using ADF and Azure Functions.
  • This includes designing embedding pipelines, vector database solutions (e.g., Azure Cognitive Search), and knowledge graph integration.

Agentic AI Implementation:

  • Lead the design and implementation of multi-agent systems using frameworks like LangChain, LangGraph.
  • Develop agents that can perform multi-step operations, use tools, and communicate with other agents to fulfill complex user requests.

LLM Integration:

  • Evaluate and select appropriate LLMs, including both hosted (Azure OpenAI) and open-source models (e.g., LLAMA), based on performance, cost, and specific task requirements.
  • Oversee prompt engineering strategies and model fine-tuning where necessary.

Azure Stack Expertise:

  • Leverage deep knowledge of the Azure AI stack, including Azure AI Search, Azure Machine Learning, Azure OpenAI Service, Azure ADF, Azure Functions, and Azure App Services, to build and deploy robust, production-ready AI solutions.

MLOps and Governance:

  • Establish and enforce MLOps best practices for the entire AI lifecycle, from continuous integration and deployment (CI/CD) to model monitoring and governance.
  • Ensure all deployments meet enterprise standards for security and reliability.

Stakeholder Collaboration:

  • Work with business leaders and internal stakeholders to gather requirements, identify new use cases, and demonstrate the business value of the chatbot solution.
  • Effectively translate complex technical concepts to non-technical audiences.

If you are interested, share the updated resume to

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