AI Architect (GenAI, RAG & Agentic AI)

Job Summary

We are seeking a highly experienced AI Architect with 15+ years of IT experience and deep expertise in architecting, designing, and deploying enterprise-scale AI platforms and solutions. The ideal candidate must possess hands-on experience across Machine Learning, MLOps, Generative AI, Retrieval-Augmented Generation (RAG), Agentic AI frameworks, LLMOps, and cloud-native AI architectures.

This role requires a strategic and technical leader capable of designing end-to-end AI ecosystems, including data pipelines, feature engineering, vector search, knowledge retrieval, LLM orchestration, multi-agent systems, AI governance, model lifecycle management, and production monitoring.

The successful candidate should have a proven track record of delivering production-grade AI solutions using modern AI platforms such as Azure OpenAI, AWS Bedrock, Google Vertex AI, LangGraph, LangChain, Vector Databases, MLflow, and enterprise MLOps frameworks.

Key Responsibilities

• Architect and deliver enterprise-scale AI, Machine Learning, and Generative AI solutions.
• Design and implement scalable RAG, Knowledge Graph, GraphRAG, and Agentic AI architectures.
• Define AI platform strategy, governance frameworks, and enterprise AI roadmaps.
• Establish and manage MLOps and LLMOps processes for model deployment, monitoring, retraining, and governance.
• Design vector search and hybrid retrieval systems leveraging structured and unstructured data.
• Build multi-agent AI systems using LangGraph, LangChain, CrewAI, AutoGen, or similar frameworks.
• Implement AI observability, model monitoring, drift detection, explainability, and performance optimization.
• Drive cloud-native AI architecture modernization on Azure, AWS, and Google Cloud Platform.
• Ensure compliance with Responsible AI, AI Security, Risk Management, and Enterprise Governance standards.
• Collaborate with business stakeholders, product teams, and engineering leadership to align AI initiatives with organizational goals.

Required Skills & Expertise

<>Generative AI & LLMs

• GPT-4/4o, Claude, Llama, Gemini, Mistral
• Prompt Engineering and LLM Orchestration
• AI Agents and Autonomous Workflows

<>RAG & Knowledge Retrieval

• Retrieval-Augmented Generation (RAG)
• Hybrid Search Architectures
• Semantic Search
• Vector Search Optimization
• GraphRAG and Knowledge Graph Solutions

<>Agentic AI

• LangGraph
• LangChain
• CrewAI
• AutoGen
• Multi-Agent Systems
• Agent Orchestration Frameworks

<>Vector Databases

• Pinecone
• Weaviate
• Qdrant
• ChromaDB
• Milvus

<>Machine Learning & MLOps

• MLflow
• Kubeflow
• Feature Stores
• Model Registry
• CI/CD for ML
• Model Monitoring
• Drift Detection
• Explainable AI (XAI)

<>Cloud AI Platforms

• Azure OpenAI
• AWS Bedrock
• Google Vertex AI
• Databricks
• Snowflake AI/ML

<>Data & Knowledge Platforms

• Neo4j
• Knowledge Graphs
• Graph Databases
• Enterprise Data Lakes
• Data Engineering for AI Workloads

<>Governance & Security

• Responsible AI
• AI Governance
• AI Risk Management
• Model Security
• Compliance Framework

Preferred Industry Experience

Candidates with experience delivering AI solutions within regulated industries are highly preferred:

• Healthcare
• Financial Services
• Banking
• Insurance
• Telecommunications
• Life Sciences

Required Qualifications

• 15+ years of overall IT experience.
• 5+ years of experience architecting AI/ML solutions in production environments.
• Strong hands-on expertise in Generative AI, RAG, Agentic AI, and enterprise AI architecture.
• Proven experience deploying and supporting AI solutions at scale.
• Experience with cloud-native AI platforms and modern MLOps practices.
• Excellent communication, stakeholder management, and leadership skills.

Important Note

Candidates must demonstrate hands-on experience architecting, deploying, and managing production AI systems. Profiles focused primarily on chatbot development, prompt engineering, proof-of-concepts, or academic AI research without enterprise-scale production implementation experience will not be considered.