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AI/ML Architect GenAI, LLMs & Enterprise Automation

AI/ML Architect GenAI, LLMs & Enterprise Automation

Simplilearn

5 - 10 years

50 - 60 Lacs

Bengaluru

Posted:1 day ago| Platform:

Apply

Skills Required

Artificial Intelligence Machine Learning AI/ML Architect Large Language Model RAG S3 Langchain Bash Scripting Pinecone Bedrock Langgraph ECS IAM Cloud FAISS AWS Lambda Python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Job Title:

Role Summary

AI/ML Architect

You will own the AI solution architecture end-to-endfrom model selection and training frameworks to infrastructure, automation, and observability. The ideal candidate will have deep expertise in GenAI systems and a strong grasp of production-grade deployment practices across the stack.

Must-Have Skills

AI/ML solution architecture experience with production-grade systems
Strong background in
LLM fine-tuning
(SFT, LoRA, PEFT) and
RAG frameworks
Experience with vector databases (FAISS, Pinecone) and embedding generation
Proficiency in
LangChain, LangGraph
, LangFlow, and prompt engineering
Deep cloud experience (AWS: Bedrock, ECS, Lambda, S3, IAM)
Infra automation using Terraform, CI/CD via GitHub Actions or CodePipeline
Backend API architecture using FastAPI or Node.js
Monitoring & observability using Langfuse, LangWatch, OpenTelemetry
Python, Bash scripting, and low-code/no-code tools (e.g., n8n)

Bonus Skills

Hands-on with multi-agent orchestration frameworks (CrewAI, AutoGen)
Experience integrating AI/chatbots into web, mobile, or LMS platforms
Familiarity with enterprise security, data governance, and compliance frameworks
Exposure to real-time analytics and event-driven architecture

You’ll Be Responsible For

Defining the AI/ML architecture strategy and roadmap
Leading design and development of GenAI-powered products and services
Architecting scalable, modular, and automated AI systems
Driving experimentation with new models, APIs, and frameworks
Ensuring robust integration between model, infra, and app layers
Providing technical guidance and mentorship to engineering teams
Enabling production-grade performance, monitoring, and governance

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