Data Scientist Agentic AI

Job Description: AI Engineer

Location: Gurgaon

Years of experience: 3-7 years

Employment Type: Full-time

About Us

We turn customer challenges into growth opportunities.

Material

Role Summary

We are looking for a highly skilled AI Engineer to build optimize and deploy production-grade AI this role you will be the engine room of our AI initiatives - taking architectural blueprints and turning them into scalable functional systems. While you will partner with Data Engineering and Platform teams your focus is on the implementation of LLM-based applications (RAG) agentic workflows and fine-tuning models to meet the specific needs of our healthcare and pharmaceutical clients.

What Youll Do

AI Development & Implementation

• Build & Optimize: Develop and maintain LLM-powered applications using frameworks like Microsoft Agent Framework AutoGen LangChain LangGraph LlamaIndex etc..
• RAG Pipelines: Implement and fine-tune Retrieval-Augmented Generation (RAG) pipelines including sophisticated chunking strategies embedding selection and vector database management.
• Agentic Systems: Develop autonomous agents capable of tool-use multi-step planning and human-in-the-loop interactions.
• Model Fine-tuning: Execute fine-tuning and optimization tasks (Quantization PEFT/LoRA) to adapt models for specific domain tasks.

MLOps & Productionization

• Deployment: Deploy models into production environments using Docker and Kubernetes ensuring high availability and low latency.
• Monitoring: Implement observability for AI systems tracking accuracy hallucinations cost and latency.
• CI/CD: Maintain CI/CD pipelines for ML ensuring automated testing (unit contract and model-quality tests) is integrated into the workflow.

Domain-Specific Execution (Pharma/Healthcare)

• Data Integrity: Work with sensitive pharmaceutical datasets ensuring all AI outputs comply with data privacy standards and PII masking requirements.
• Validation: Support the rigorous validation processes required in life sciences including reproducibility and statistical validity of model outputs.

Collaboration & Mentorship

• Teamwork: Work closely with Senior Architects and Engagement Managers to translate business requirements into technical tasks.
• Code Quality: Participate in code reviews and contribute to the teams internal library of reusable AI patterns and playbooks.

Must-Have Qualifications

• Experience: 3-7 years of experience in Software Engineering or Data Science with at least 2 years focused specifically on deploying AI/ML models in production.
• Tech Stack: Expert-level Python skills and proficiency with deep learning frameworks (PyTorch or TensorFlow).
• Generative AI: Hands-on experience building applications with LLMs (OpenAI Claude Gemini etc.) and vector databases.
• Cloud & DevOps: Strong experience with AWS/Azure/GCP and containerization (Docker/Kubernetes).
• Engineering Fundamentals: Strong SQL skills API design (FastAPI/Flask) and a software engineering first approach to ML (testing modularity and documentation).

Preferred Qualifications

• Pharma Experience: Prior experience working with healthcare data clinical trials or life sciences digital transformation.
• Advanced RAG: Experience with advanced retrieval techniques (reranking hybrid search query expansion).
• Evaluation Frameworks: Experience using G-Eval RAGAS or TruLens to quantify LLM performance.
• Performance Tuning: Knowledge of vLLM DeepSpeed or Triton Inference Server for high-throughput serving.