Data Scientist - Artificial Intelligence

Data Scientist - AI

Engineering - Full-Time - On-site

Experience :

3 - 5 years

Location :

Mohali/Noida

ABOUT THE ROLE :

We are hiring a Senior AI Engineer to lead the design, development, and deployment of AI-powered systems across our engineering platform. You will work at the intersection of applied machine learning, software engineering, and product delivery - building systems that directly impact how our teams ship software and serve customers.

This is a high-ownership role.

You will not just integrate AI APIs - you will own the end-to-end lifecycle of AI features, from research and prototyping through production reliability.

KEY RESPONSIBILITIES :

• Design and implement LLM-powered features including agents, RAG pipelines, and evaluation frameworks integrated into production systems.

• Ownership. Own the full AI feature lifecycle:

• Prototype, evaluate, and deploy ML models and AI services - including fine-tuning, prompt engineering, and model selection.

• Build and maintain robust data pipelines for model training, evaluation, and monitoring using tools such as Airflow, dbt, or Spark.

• Define and enforce AI quality standards - including automated evals, red-teaming, and latency/accuracy benchmarking.

• Collaborate with product, design, and infrastructure teams to ship AI features that are reliable, explainable, and scalable.

• Establish best practices for AI tooling, code review for ML code, and engineering standards across the AI function.

• Mentor engineers on applied AI techniques, model evaluation, and responsible AI usage.

• Contribute to vendor assessment - including evaluation of AI tools such as Cursor, Claude, GitHub Copilot, and internal LLM deployments.

REQUIRED QUALIFICATIONS :

• 3 - 5 years of software engineering experience, with at least 2 years focused on AI/ML systems in production.

• Deep proficiency in Python; familiarity with TypeScript or Go is a plus.

• Hands-on experience with LLM frameworks - LangChain, LangGraph, etc.

• Experience building RAG systems, vector databases (Pinecone, Weaviate, pgvector), and semantic search pipelines.

• Strong understanding of model evaluation - offline evals, human feedback loops, A/B testing, and hallucination detection.

• Proficiency with cloud AI services (AWS SageMaker, Azure ML, or GCP Vertex AI) and container-based deployments.