GenAI Architect
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Role details
Tech stack
Job description
- Owns end to end client delivery for the project team
Owns end-to-end technical direction and client alignment for the agentic AI platform.
Primary technical interface with the client, translating business requirements into architecture spanning RAG pipelines, MCP connectors, and hybrid orchestration across Appian, ERP, DealCloud, Backstop CRM, Snowflake, and Graph DB.
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Project Prioritization and SPOC for Persistent for any queries
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Stakeholder mgmt
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Risk mgmt
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Participate in status report and governance meet.
Lead architecture across all AI layers: RAG, MCP connectors (action/data), agent orchestration
Define integration strategy leveraging existing client APIs, minimising custom build
Drive MCP connector design for Appian, ERP, DealCloud, Backstop, Snowflake, Graph DB
Own RAG pipeline decisions: chunking strategy, embedding model, Pinecone retrieval, re-ranking
Collaborate with client stakeholders (business + IT) to validate use cases
Guide the offshore team (AI/ML engineers, data engineers)
Requirements
12+ years software/AI engineering; 1-2+ years enterprise AI or agentic system design
Hands-on RAG: LlamaIndex or LangChain, Pinecone, Azure OpenAI
Strong API integration: REST, OAuth
MCP / tool-layer design for LLM agents; FASTMCP a strong plus
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Prepare application
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