GENAI Solution Architect

Role Summary

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, Deal Cloud, Backstop CRM, Snowflake, and Graph DB.

Key Responsibilities

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)

Technology Stack

8-10+ years software/AI engineering; 1-2+ years enterprise AI or agentic system design

Hands-on RAG: Llama Index or LangChain, Pinecone, Azure OpenAI

Strong API integration: REST, OAuth

MCP / tool-layer design for LLM agents; FASTMCP a strong plus

Financial services platforms (Deal Cloud, Backstop, or similar) advantageous

Preferred Skills

Experience building AI platforms / control planes / orchestration layers

Exposure to low-code/no-code platforms (Appian or similar)

Experience with AI governance, LLMOps, and enterprise AI rollout

Familiarity with map-based or data visualization platforms and with Neo4j / Cosmos DB

Experience & Profile

12–15 years in enterprise architecture and solution design

Proven experience in end-to-end system design and large-scale implementations