Data Scientist - Agentic AI Developer

Senior Data Scientist Agentic AI, LLMs, Databricks & AWS Bedrock

Experience: 6–8 years

Role Type: Individual Contributor

Primary Focus: Data Science, Generative AI, LLMs and Agentic AI

Domain: Manufacturing, Industrial or Supply Chain experience is an added advantage

Job Overview

We are looking for a hands-on Senior Data Scientist with strong experience in traditional machine learning, Generative AI, LLMs and Agentic AI. The candidate will own the complete data science lifecycle, from understanding business problems and exploring data to developing, deploying and monitoring production-ready AI solutions.

This role requires strong expertise in Python, Databricks and AWS Bedrock, along with the ability to build models and AI applications from first principles rather than relying only on AutoML or pre-built components.

Key Responsibilities

• Partner with business and technical stakeholders to define problems, success metrics, KPIs and solution approaches.
• Perform data sourcing, EDA, statistical analysis, feature engineering, data-quality checks and hypothesis testing.
• Build and evaluate machine learning, deep learning, time-series, anomaly-detection, recommendation and optimization models.
• Develop production-ready LLM, RAG and Agentic AI applications using frameworks such as LangGraph, LangChain, Amazon Bedrock Agents or similar.
• Design agent workflows involving tool calling, state and memory management, human-in-the-loop approvals, retries, fallbacks and MCP integrations.
• Build secure and scalable solutions using Databricks Apps, MLflow, Model Serving, Vector Search, Delta Lake and Unity Catalog.
• Develop applications on Amazon Bedrock using foundation models, Knowledge Bases, Agents, Guardrails, prompt management and model evaluation.
• Design advanced RAG pipelines involving hybrid retrieval, metadata filtering, re-ranking, query rewriting and retrieval evaluation.
• Build NLP solutions for text classification, NER, information extraction, semantic search and document summarization.
• Develop computer vision solutions for classification, object detection, segmentation, OCR and visual defect inspection.
• Fine-tune LLMs, embedding and vision models using LoRA, QLoRA, PEFT and Hugging Face frameworks.
• Deploy AI services using FastAPI, Docker, Lambda, API Gateway, ECS/EKS and CI/CD pipelines.
• Monitor model performance, drift, quality, latency and cost, and communicate findings and recommendations to stakeholders.

Required Skills

• 6–8 years of Data Science experience, including at least 3 years of hands-on Generative AI experience.
• At least 5 years of advanced Python development experience.
• Strong expertise in Python, Pandas, NumPy, PySpark, SQL and object-oriented programming.
• Strong foundations in statistics, probability, machine learning, deep learning and model evaluation.
• Experience with Scikit-learn, XGBoost, LightGBM and PyTorch or TensorFlow.
• Hands-on experience building LLM applications using Claude through Amazon Bedrock or other foundation models.
• Strong understanding of prompt engineering, structured outputs, function/tool calling, context management, caching and LLM evaluation.
• Proven experience building at least one end-to-end multi-step or multi-agent system.
• Experience with agent tool design, state, memory, human-in-the-loop workflows, evaluation, tracing and MCP.
• Experience with RAG, embeddings, vector databases, hybrid search, re-ranking and retrieval metrics such as recall@k, MRR and nDCG.
• Hands-on experience with Databricks Apps, MLflow, Model Serving, Vector Search, Workflows, Delta Lake and Unity Catalog.
• Hands-on experience with AWS Bedrock, S3, IAM, Lambda, API Gateway, OpenSearch, SageMaker and CloudWatch.
• Experience with FastAPI, REST APIs, Git, Docker, automated testing, CI/CD and Infrastructure as Code.
• Strong stakeholder communication and the ability to explain technical trade-offs to business and engineering teams.