Job Title: GenAI Architect

Experience

10–15+ Years

Location

Hybrid / Remote

Role Overview

We are seeking a highly experienced GenAI Architect to lead the design, development, and deployment of enterprise-scale Generative AI solutions. The ideal candidate will possess deep expertise in AI architecture, multi-agent systems, RAG pipelines, cloud-native application development, MLOps/LLMOps, and healthcare-compliant AI systems.

The role requires robust technical leadership, architecture governance, stakeholder management, and hands-on experience building production-grade AI platforms on Azure and AWS.

Key Responsibilities

1. Architecture and System Design

- Define end-to-end architecture for enterprise AI platforms and GenAI applications.
- Design scalable, secure, highly available distributed systems.
- Create architecture blueprints, solution designs, and technical roadmaps.
- Establish architecture standards, governance frameworks, and best practices.

2. Multi-Agent System Design

- Design and implement autonomous AI agent ecosystems.
- Develop agent orchestration frameworks and agent collaboration workflows.
- Build planning, reasoning, memory, and tool-calling capabilities.
- Evaluate and integrate agent frameworks such as LangGraph, AutoGen, CrewAI, Semantic Kernel, and custom orchestration solutions.

3. RAG Pipeline Architecture

- Architect enterprise Retrieval-Augmented Generation (RAG) systems.
- Design document ingestion, chunking, embedding, indexing, retrieval, reranking, and response generation workflows.
- Implement vector database architectures using Pinecone,



Azure AI Search, Weaviate, Chroma, FAISS, or Elasticsearch.
- Optimize retrieval accuracy, latency, observability, and cost.

4. FastAPI / Python Backend Development

- Design scalable Python microservices using FastAPI.
- Build APIs for LLM applications, agents, and AI workflows.
- Implement authentication, authorization, rate limiting, and API security.
- Optimize backend performance for high-volume AI workloads.

5. Frontend Architecture

- Define architecture for AI-powered web applications.
- Collaborate with frontend teams using React, Next.js, Angular, or similar frameworks.
- Design conversational interfaces, agent dashboards, and AI workflow monitoring portals.
- Ensure responsive, scalable, and secure frontend solutions.

6. Database Design at Scale

- Design relational and NoSQL database architectures.
- Optimize data models for AI workloads and enterprise-scale applications.
- Implement caching, data partitioning, and performance tuning strategies.
- Work with PostgreSQL, SQL Server, Cosmos DB, MongoDB, Redis, and vector databases.

7. MLOps and LLMOps

- Establish CI/CD pipelines for AI model deployment.
- Implement model monitoring, observability, evaluation, and governance.




- Design prompt management, versioning, experimentation, and deployment frameworks.
- Build automated workflows for model lifecycle management.

8. Cloud Architecture (Azure Primary + AWS)

- Architect cloud-native AI platforms on Azure and AWS.
- Design secure, scalable infrastructure using Infrastructure as Code.
- Utilize services such as:
- Azure OpenAI
- Azure AI Studio
- Azure AI Search
- Azure Kubernetes Service (AKS)
- AWS Bedrock
- AWS SageMaker
- Amazon OpenSearch
- Amazon EKS

- Implement disaster recovery, security, and compliance controls.

9. Healthcare Domain and HIPAA Compliance

- Design AI solutions aligned with healthcare regulations.
- Ensure HIPAA-compliant data handling and governance.
- Implement secure PHI processing, encryption, auditing, and access controls.
- Collaborate with healthcare stakeholders to build compliant AI products.

10. Architecture Decision-Making Artifacts

- Create and maintain:
- Solution Architecture Documents (SAD)
- High-Level Designs (HLD)
- Low-Level Designs (LLD)
- Architecture Decision Records (ADR)
- Technical Standards Documents
- Risk and Compliance Assessments

11. Leadership and Stakeholder Communication

- Provide technical leadership across engineering teams.
- Mentor architects, engineers, and AI practitioners.
- Present architecture strategies to executive leadership.
- Drive technical discussions with business, product, security, and compliance stakeholders.
- Lead architecture reviews and governance boards.

📌 UHG AI Architect (Bengaluru)
🏢 TalentOla
📍 Bengaluru