Data Scientist - Agentic AI Developer

Cai Info India; Bengaluru; À distance; INR 900 000 - 1 500 000; Plein temps

Résumé du poste

Cai Info India is seeking a Data Scientist - Agentic AI Developer to design, deploy, and monitor production-ready ML and Generative AI solutions. The role is fully remote, allowing flexible work arrangements while delivering impact across client projects.

Ideal candidates will have 6–8 years of Data Science experience with strong Python expertise, Databricks, and experience with AWS Bedrock. You will build end-to-end AI workflows, multi-agent systems, and scalable AI services.

Qualifications

• 6 to 8 years of Data Science experience with at least 3 years in Generative AI.
• At least 5 years of advanced Python development experience.
• Strong expertise in Python, Pandas, NumPy, PySpark, SQL, and object-oriented programming.
• Solid 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 end-to-end multi-step or multi-agent systems.

Responsabilités

• 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.

Connaissances

Python

Pandas

NumPy

PySpark

SQL

ML Fundamentals

Statistical Analysis

Problem Solving

Communication

Formation

Master's or PhD in CS/Math/Stats

Outils

Databricks

AWS Bedrock

LangGraph

LangChain

MLflow

Docker

FastAPI

Description du poste

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,

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 evaluationData 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,

  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

  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,