Data Scientist - Agentic AI Developer
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Before you apply
LocationIndia - Bengaluru
Work moderemote
Typefull-time
SenioritySenior
Experience6–8 yrs
Company size5,001–10,000 people
PostedOct 23, 2026 · 2w ago
Verified live3d ago
At a glanceSummarised by Seekless from the posting.
6 to 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, hypothesis testing, and model evaluation
Hands-on experience with Scikit-learn, XGBoost, LightGBM, and PyTorch or TensorFlow
Experience building models and AI applications from first principles rather than relying only on AutoML or pre-built components
Hands-on experience building LLM applications using Claude through Amazon Bedrock or other foundation models
Strong understanding of prompt engineering, structured outputs, function and 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 and memory management, human-in-the-loop workflows, retries, fallbacks, evaluation, tracing, and MCP
Experience with RAG, embeddings, vector databases, hybrid search, metadata filtering, re-ranking, and query rewriting
Knowledge of retrieval evaluation metrics including 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
Experience deploying and monitoring production-ready machine learning and Generative AI solutions
Strong stakeholder communication skills and the ability to explain technical trade-offs to business and engineering teams
Experience developing NLP solutions including text classification, named entity recognition, information extraction, semantic search, and document summarization
Experience developing computer vision solutions including classification, object detection, segmentation, OCR, and visual defect inspection
Experience fine-tuning LLMs, embedding models, or vision models using LoRA, QLoRA, PEFT, or Hugging Face
Experience deploying containerized AI services using ECS or EKS
Experience working on enterprise-scale AI solutions in manufacturing, industrial, engineering, or supply chain environments
Skills
Python
Pandas
NumPy
PySpark
SQL
Scikit-learn
XGBoost
LightGBM
PyTorch
TensorFlow
LangGraph
LangChain
Databricks
MLflow
AWS Bedrock
AWS S3
AWS IAM
AWS Lambda
AWS API Gateway
AWS OpenSearch
AWS SageMaker
AWS CloudWatch
FastAPI
REST APIs
Git
Docker
CI/CD
Hugging Face
AWS ECS
AWS EKS
About the role
Data Scientist - Agentic AI Developer
Req number:
R8813
Employment type:
Full time
Worksite flexibility:
Remote
Who we are
CAI is a global services firm with over 9,000 associates worldwide and a yearly revenue of $1.3 billion+. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients, colleagues, and communities. As a privately held company, we have the freedom and focus to do what is right—whatever it takes. Our tailor-made solutions create lasting results across the public and commercial sectors, and we are trailblazers in bringing neurodiversity to the enterprise.
Job Summary
We are looking for a motivated Data Scientist - Agentic AI Developer ready to take us to the next level! If you have advanced Python, Databricks, and AWS Bedrock experience and are looking for your next career move, apply now
Job Description
We are looking for a Data Scientist - Agentic AI Developer to develop, deploy, and monitor production-ready machine learning, Generative AI, LLM, RAG, and Agentic AI solutions. This position will be full-time and remote.
What You’ll Do
•
Partner with business and technical stakeholders to define problems, success metrics, KPIs, constraints, and solution approaches
•
Perform data sourcing, exploratory data analysis, 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 LangGraph, LangChain, Amazon Bedrock Agents, or similar frameworks
•
Design multi-step and multi-agent workflows involving tool calling, state and memory management, human-in-the-loop approvals, retries, fallbacks, tracing, and MCP integrations
•
Build secure and scalable AI solutions using Databricks Apps, MLflow, Model Serving, Vector Search, Workflows, 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, embeddings, vector databases, and retrieval evaluation
•
Build NLP solutions for text classification, named entity recognition, 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 models, and vision models using LoRA, QLoRA, PEFT, and Hugging Face frameworks
•
Develop and deploy AI services using FastAPI, REST APIs, Docker, Lambda, API Gateway, ECS, EKS, and CI/CD pipelines
•
Monitor model performance, drift, quality, latency, reliability, and cost
•
Conduct error analysis, model evaluation, and continuous improvement based on technical and business metrics
•
Communicate technical findings, trade-offs, risks, and recommendations to business and engineering stakeholders
What You’ll Need
Required:
•
6 to 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, hypothesis testing, and model evaluation
•
Hands-on experience with Scikit-learn, XGBoost, LightGBM, and PyTorch or TensorFlow
•
Experience building models and AI applications from first principles rather than relying only on AutoML or pre-built components
•
Hands-on experience building LLM applications using Claude through Amazon Bedrock or other foundation models
•
Strong understanding of prompt engineering, structured outputs, function and 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 and memory management, human-in-the-loop workflows, retries, fallbacks, evaluation, tracing, and MCP
•
Experience with RAG, embeddings, vector databases, hybrid search, metadata filtering, re-ranking, and query rewriting
•
Knowledge of retrieval evaluation metrics including 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
•
Experience deploying and monitoring production-ready machine learning and Generative AI solutions
•
Strong stakeholder communication skills and the ability to explain technical trade-offs to business and engineering teams
Nice to have
Preferred:
•
Experience developing NLP solutions including text classification, named entity recognition, information extraction, semantic search, and document summarization
•
Experience developing computer vision solutions including classification, object detection, segmentation, OCR, and visual defect inspection
•
Experience fine-tuning LLMs, embedding models, or vision models using LoRA, QLoRA, PEFT, or Hugging Face
•
Experience deploying containerized AI services using ECS or EKS
•
Experience working on enterprise-scale AI solutions in manufacturing, industrial, engineering, or supply chain environments
Physical Demands
•
Ability to safely and successfully perform the essential job functions
•
Sedentary work that involves sitting or remaining stationary most of the time with occasional need to move around the office to attend meetings, etc.
•
Ability to conduct repetitive tasks on a computer, utilizing a mouse, keyboard, and monitor
Reasonable accommodation statement
If you require a reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employment selection process, please direct your inquiries to [email protected] or (888) 824 – 8111.