Data Scientist - Agentic AI Developer

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

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.