Gen AI Architect

TRole Overview

We are seeking a GenAI Solution Architect / AI Data Architect with deep expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI-first data architecture, and large-scale data engineering platforms. The ideal candidate will be responsible for designing end-to-end AI and data ecosystems that support enterprise-grade GenAI applications, while providing overall technical leadership across solution architecture, data platforms, security, and scalability.

Key Responsibilities

• Define system architecture tailored for LLM execution, managing multi-layer database models (raw, stg, core, fact, mart) and context window design in close collaboration with the client POC
• Architect resilient ingestion pipelines for high-volume public APIs, BigQuery historical backfills, social scrapers, and AI-driven entity resolution engines.
• Establish strict physical data boundary rules between shared data pools and isolated client environments.
• Set protocols for system fallback behaviour, rate-limiting, cost caps, and agentic health monitoring.
• Deep expertise in AI-era database architecture (BigQuery/SQL), prompt/system design, data security, and high-throughput data pipelines, RAG systems
• Prepare HLD/LLD/Deployment diagram and other required documentation with the support from tech lead
• Provide overall technical oversight to the team
• Brainstorming with the client POCs for the future roadmap, create prototypes to check feasibility of upcoming GenAI innovations in the industry
• Mentor team in overall GenAI solutioning to ensure they are following industry best practices

Required Skills & Experience

• 12+ years of experience in solution architecture, data engineering, or enterprise application development.
• Strong expertise in Generative AI, Large Language Models (LLMs), Agentic AI systems, and Retrieval-Augmented Generation (RAG).
• Hands-on experience designing AI architectures using modern LLM ecosystems and prompt engineering techniques.
• Strong experience building high-throughput, fault-tolerant ETL/ELT and streaming data pipelines.
• Experience with vector databases, embeddings, semantic search, hybrid retrieval, and knowledge graph solutions.
• Hands-on experience with LangChain, LangGraph, LlamaIndex, MCP, or similar AI orchestration frameworks.
• Understanding of AI system monitoring, evaluation frameworks, hallucination mitigation, guardrails, and model governance.

Preferred Qualifications

• Experience building enterprise AI platforms leveraging BigQuery, Vertex AI, Gemini, OpenAI, Claude, or equivalent LLM platforms.
• Exposure to AI agents, autonomous workflows, multi-agent systems, and agent orchestration frameworks.
• Knowledge of MLOps, LLMOps, CI/CD pipelines, model lifecycle management, and AI observability tools.
• Experience in data lineage, metadata management, and enterprise data governance frameworks.
• Prior experience leading GenAI transformation initiatives or innovation programs within enterprise environments.