Data Science Engineer Agentic AI (Enterprise Data), (Inperson Interview mandatory)

Job Title: Data Science Engineer – Agentic AI (Enterprise Data)

Location: Alpharetta, GA (Hybrid)
Interview Mode:In-Person Interview Required, Atlanta, GA, Dallas, TX, Bay area, CA, Chicago, IL NYC, Charlotte, NC
Duration:Long Term – Initial 12 Months (with extension possible)

Job Summary

We are seeking a highly skilled Data Science Engineer – Agentic AI to design, build, and deploy intelligent, autonomous AI agents that work with large-scale enterprise data. The ideal candidate will have strong expertise in data science, machine learning, and modern AI frameworks, with hands-on experience building agent-based systems that can reason, plan, and act across complex business workflows.

Key Responsibilities

• Design and develop Agentic AI systems that autonomously interact with enterprise data and applications

• Build and optimize machine learning and deep learning models for structured and unstructured data

• Develop AI agents using frameworks such as LangChain, AutoGen, CrewAI, or similar

• Integrate AI agents with enterprise data platforms (data lakes, warehouses, APIs, databases)

• Perform data ingestion, preprocessing, feature engineering, and model evaluation

• Implement LLM-based solutions for analytics, decision support, and automation use cases

• Collaborate with data engineers, architects, and business stakeholders to translate requirements into AI solutions

• Ensure model performance, scalability, security, and compliance with enterprise standards

• Deploy models and agents into production using MLOps best practices

• Monitor, fine-tune, and continuously improve deployed AI solutions

Required Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related field

• 5+ years of experience in Data Science / Machine Learning Engineering

• Strong proficiency in Python (NumPy, Pandas, Scikit-learn)

• Hands-on experience with LLMs (OpenAI, Azure OpenAI, Anthropic, etc.)

• Experience building Agentic AI / autonomous agents

• Solid understanding of statistics, probability, and ML algorithms

• Experience working with enterprise data (SQL, NoSQL, data lakes, data warehouses)

• Knowledge of cloud platforms (AWS, Azure, or Google Cloud Platform)

• Experience with REST APIs and microservices

• Strong problem-solving and communication skills

Preferred / Nice-to-Have Skills

• Experience with LangChain, AutoGen, CrewAI, Semantic Kernel

• Knowledge of vector databases (Pinecone, FAISS, Weaviate, Chroma)

• Experience with MLOps tools (MLflow, Kubeflow, Airflow)

• Familiarity with Spark, Databricks, or large-scale data processing

• Experience in RAG (Retrieval-Augmented Generation) architectures

• Exposure to data governance, security, and compliance in enterprise environments