Datagaps is the only company to be listed in Gartner® DataOps Tools & Data Observability market guides

Agentic AI Lead

Skills & Technologies

Python

LLMs

LangChain

GenAI

Data Engineering

Apache Spark

Share:

What You'll Bring

10+ years of experience in Data Engineering, AI-driven Data Platforms, or Product Engineering, with at least 4–5+ years focused on AI/ML, Generative AI, or Agentic AI architectures.
Proven track record in applying AI to automate and enhance data validation, quality, and observability workflows.
Deep expertise in LLMs, Autonomous AI agents, and GenAI frameworks such as LangChain, LangGraph, Azure AI Foundry, AWS Bedrock, or OpenAI APIs.
Hands-on experience in designing AI-powered validation systems, including schema intelligence, anomaly detection, reconciliation, and auto-healing pipelines.
Strong programming background in Python, SQL, and Spark, with knowledge of AI workflow orchestration tools (e.g., Airflow, dbt, Prefect).
Solid understanding of vector databases, retrieval-augmented generation (RAG), and metadata-driven AI validation frameworks.
Experience integrating Data Quality and Observability tools (e.g., Great Expectations, Soda, Monte Carlo, Datagaps) with AI or ML-driven validation logic.
Strong architectural understanding of data pipelines, model governance, and AI-assisted data testing frameworks.
Strong leadership and communication skills to bridge AI innovation, data engineering, and product strategy.

What You'll Do

What We Offer

Leave us your info

Fill in the details below and we’ll be in touch soon. Fields marked * are required.