AI Architect

Saransh Inc; Hyderabad; On-site; INR 6,000,000 - 11,000,000; Full time

Job summary

Saransh Inc in Hyderabad is seeking an AI Architect to lead GenAI and Agentic AI initiatives within an enterprise AI CoE. The role demands 15+ years in software engineering or architecture, with deep hands-on GenAI, LLMs, and BFSI domain experience.

You will design scalable, secure AI architectures, implement AI-driven SDLC, and drive large-scale AI transformations across the organization. Key tech include Java, LangChain, LangGraph, AutoGen and CrewAI, plus cloud, Kubernetes and MLOps.

Qualifications

• 15+ years in Software Engineering / Architecture.
• Hands-on GenAI, LLMs & Agentic AI expertise.
• BFSI / Financial Services domain experience mandatory.
• Strong Java programming and enterprise architecture skills.
• Hands-on with RAG, embeddings and prompt engineering.
• Experience with multi-agent AI systems and AI-driven SDLC.
• Proficient in LangChain/LangGraph/AutoGen/CrewAI.
• Cloud (AWS/Azure/GCP), Kubernetes, Docker and microservices.
• Secure, scalable, production-grade AI architectures.

Skills

Agentic AI

RAG

Multi Agent AI

GenAI

LLMs

Java

AI Architect

MLOps

LLMOps

AI Observability

Explainability

Guardrails

Tools

LangChain

LangGraph

AutoGen

CrewAI

Kubernetes

Docker

APIs

AWS

Azure

GCP

Job description

Hiring: AI Architect – GenAI & Agentic AI

Role: AI Architect / GenAI Architect

Experience: 15+ Years

Mandate Skills: Agentic AI, RAG, Multi Agent AI, Java

We are looking for an experienced AI Architect to join an enterprise AI Center of Excellence (CoE) and drive large-scale AI transformation across the organization.

Key Requirements:

• 15+ years of overall experience in Software Engineering / Architecture
• Strong hands‑on experience in GenAI, LLMs & Agentic AI
• BFSI / Financial Services domain experience is mandatory
• Strong Java programming and enterprise architecture experience
• Hands‑on experience with RAG, Embeddings & Prompt Engineering
• Strong experience in multi‑Agent AI systems
• Experience with LangChain / LangGraph / AutoGen / CrewAI
• Experience with AI‑driven SDLC and DevOps / CI-CD integration
• Strong understanding of AI Observability, Explainability & Guardrails
• Experience with AI Security, Governance, Responsible AI & Data Privacy
• Hands‑on experience with MLOps / LLMOps
• Experience with AWS / Azure / GCP
• Strong experience with Kubernetes, Docker, Microservices & APIs
• Experience designing scalable, secure and production‑grade AI architectures

Good to Have

• Experience building Internal Developer Platforms (IDPs)
• AI accelerators, reference architectures & enterprise AI playbooks
• Experience in regulated BFSI environments