Job Title : AI / ML Architect - GenAI, LLMs & Enterprise Automation
Location : Bangalore
Experience : 8+ years (including 4+ years in AI / ML architecture on cloud platforms)
Role Summary
We are seeking an experienced AI / ML Architect to define and lead the design, development, and scaling of GenAI-driven solutions across our learning and enterprise platforms. This is a senior technical leadership role where you will work closely with the CTO and product leadership to architect intelligent systems powered by LLMs, RAG pipelines, and multi-agent orchestration.
You will own the AI solution architecture end-to-end-from 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 platformsFamiliarity with enterprise security, data governance, and compliance frameworksExposure to real-time analytics and event-driven architectureYou'll Be Responsible For
Defining the AI / ML architecture strategy and roadmapLeading design and development of GenAI-powered products and servicesArchitecting scalable, modular, and automated AI systemsDriving experimentation with new models, APIs, and frameworksEnsuring robust integration between model, infra, and app layersProviding technical guidance and mentorship to engineering teamsEnabling production-grade performance, monitoring, and governance(ref : iimjobs.com)