AI Technical Lead / Architect

RGBSI; Bengaluru; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

RGBSI is seeking an experienced software architect to lead the design and delivery of customer-facing AI applications. The role covers new product development, AI enablement of existing products, and ensuring performance, security, and governance throughout production deployment.

The candidate should bring extensive experience in the .NET stack, frontend frameworks, and a security-first mindset for scalable enterprise solutions.

Qualifications

• 4+ years in software architecture with 2+ years in production agentic AI systems.
• Proven track record deploying agentic AI solutions at scale.
• Deep expertise in .NET ecosystem and modern frontend frameworks.

Responsibilities

• Lead end-to-end development of customer-facing AI applications from architecture design through production deployment.
• New Product Development
• AI Enablement of Existing Products
• Performance, Security and Governance

Skills

Software architecture

Agentic AI systems

Production deployment

.NET ecosystem

Frontend frameworks

Security mindset

Prompt engineering

Model fine-tuning

AI observability

Vector databases

LangChain/LangGraph

Tools

Angular

TypeScript

Python

RESTful APIs

Microservices

OAuth 2.0

Azure

AWS

Docker

Kubernetes

CI/CD

LangChain

LangGraph

AutoGen

CrewAI

Anthropic Claude

Azure AI Foundry

OpenAI

Job description

Role & responsibilities

• Lead end-to-end development of customer-facing AI applications from architecture design through production deployment.
• New Product Development
• AI Enablement of Existing Products
• Performance, Security and Governance

Preferred candidate profile

You Bring:

• 4+ years in software architecture with 2+ years in production Agentic AI Systems
• Proven track record deploying agentic AI solutions at scale
• Deep expertise in .NET ecosystem and modern frontend frameworks
• Security-first mindset for enterprise applications
• Experience with prompt engineering, model fine-tuning, and AI observability
• Experience with function calling, semantic search, streaming responses, and AI cost optimization.

• AI Frameworks: LangChain, LangGraph, AutoGen, CrewAI, or similar agentic frameworks
• LLM Integration: Anthropic Claude, Azure AI Foundry, OpenAI, AWS Bedrock
• Backend: .NET Core (C#), Python, RESTful APIs, microservices architecture
• Frontend: Angular, TypeScript, real-time UI for AI interactions
• Vector DBs: Pinecone, Weaviate, ChromaDB, or Qdrant
  Cloud & DevOps: Azure/AWS, Docker, Kubernetes, CI/CD pipelines
• Security: OAuth 2.0, API security, data encryption, compliance (SOC2, GDPR)
• Orchestration: Multi-agent workflows, tool calling, RAG (Retrieval-Augmented Generation), Chain of Thoughts