Applied AI / LLM Systems Engineer

Location: Gurgaon

Team: AI/ML

Role Overview

We are looking for a highly skilled Applied AI Engineer to build and deploy production-grade AI systems across forecasting, data intelligence, and LLM-powered automation.This role focuses on designing agentic AI systems, data pipelines, and predictive models that directly power business decision-making. You will work on building systems such as price intelligence engines, automated data pipelines, forecasting models, and LLM-powered decision agents.The ideal candidate combines solid ML fundamentals, software engineering rigor, and experience deploying AI systems in production.

Key Responsibilities
- Build Production AI Systems
- Design and deploy LLM-powered agent systems using frameworks like LangGraph, AutoGen, or LangChain
- Build AI pipelines integrating structured data, APIs, and external sources
- Implement RAG architectures for knowledge-driven applications

ML Infrastructure & Deployment
- Deploy models using:
- Docker
- Kubernetes
- FastAPI
- AWS / GCP
- Build scalable ML pipelines




- Implement model monitoring and performance tracking

AI Product Development
- Convert business problems into AI-driven solutions
- Build decision-support tools powered by ML models
- Work closely with leadership to implement AI-first workflows

Required SkillsCore AI / ML
- Strong experience with Python
- Machine learning frameworks:
- PyTorch
- Scikit-learn
- LightGBM / XGBoost
- Experience building time-series forecasting models

LLM Systems
- Experience building applications with:
- LangChain
- LangGraph
- AutoGen
- Experience with RAG architectures
- Familiarity with open-source models such as:
- LLaMA
- Mistral
- Mixtral

Data Engineering
- SQL and data modeling
- ETL pipeline development
- Web scraping and API integrations

Infrastructure
- Docker
- Cloud platforms (AWS/GCP/Azure)
- CI/CD pipelines

Good to Have
- Experience with agentic AI systems
- Vector databases (Pinecone, Weaviate, F

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