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AI Architect
AI ArchitectDexian India • bhubaneswar, India
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AI Architect

AI Architect

Dexian India • bhubaneswar, India
2 days ago
Job description

About the Role

We are looking for an experienced AI / ML Architect to lead the design and implementation of advanced Generative AI and RAG (Retrieval-Augmented Generation) solutions. The role combines hands-on architecture design, pre-sales engagement, and technical leadership across enterprise AI initiatives.

You will drive solutioning around LLMs, knowledge retrieval, and MCP-based multi-agent architectures, helping customers unlock business value from AI responsibly and at scale.

Key Responsibilities

  • Architect and deliver enterprise-grade AI / ML & Generative AI solutions, including RAG pipelines, LLM integrations, and intelligent agents.
  • Engage in pre-sales activities : collaborate with business development, present technical solutions, estimate effort, and support proposals / PoCs for prospects.
  • Design knowledge retrieval layers using vector databases (FAISS, Pinecone, Milvus, Chroma, Weaviate).
  • Develop document ingestion, embedding, and context-retrieval pipelines for unstructured and structured data.
  • Architect and manage MCP (Model Context Protocol) servers for secure context exchange, multi-model orchestration, and agent-to-agent collaboration.
  • Define LLMOps / MLOps best practices – CI / CD for models, prompt versioning, monitoring, and automated evaluation.
  • Collaborate with pre-sales and business teams to shape AI solution proposals, PoCs, and client demos.
  • Lead AI innovation initiatives and mentor technical teams on GenAI, RAG, and MCP frameworks.
  • Ensure data privacy, compliance, and responsible AI across all deployments
  • Work closely with ITS, TIC team to provide mentorship and guidance to AI developers

Required Skills & Experience

  • 12–15 years of overall experience with 5–7 years in AI / ML and 3+ years in Generative AI / LLM architecture.
  • Strong hands-on experience with RAG pipelines, vector search, and semantic retrieval.
  • Proven experience integrating LLMs (OpenAI, Claude, Gemini, Mistral, etc.) using frameworks such as LangChain, LlamaIndex, or PromptFlow.
  • Deep understanding of MCP servers – configuration, context routing, memory management, and protocol-based interoperability.
  • Strong programming skills in Python, and familiarity with containerization (Docker, Kubernetes) and cloud AI services (Azure OpenAI, AWS Bedrock, GCP Vertex AI).
  • Expertise in MLOps / LLMOps tools (MLflow, KubeFlow, LangSmith, Weights & Biases).
  • Solid grounding in data engineering, pipelines, and orchestration tools (Airflow, Prefect).
  • Excellent communication, client engagement, and technical presentation skills
  • Proven track record of practice building or leadership in emerging technology domains

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