AI Technical Architect

RGBSI; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

RGBSI in Bengaluru is seeking a skilled professional to lead the end-to-end development of customer-facing AI applications. You will be pivotal in new product development while ensuring performance, security, and governance in AI systems.

The ideal candidate should have over 6 years of software architecture experience, including at least 2 years with Agentic AI Systems and a proven track record in deploying such solutions at scale. Proficiency in the .NET ecosystem and modern frontend frameworks are essential.

Qualifications

• 6+ 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.
• Engage in new product development.
• Ensure performance, security, and governance.

Skills

AI application development

Software architecture

.NET ecosystem

AI observability

Microservices architecture

Tools

Angular

Docker

Kubernetes

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:

• 6+ 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