Senior Data Scientist / AI Engineer

Job Description

Seeking a Senior Data Scientist with hands-on experience in GenAI agent development and modern AI engineering. The focus is on building production-grade agents, MCP integrations, and enterprise knowledge systems using cloud and data stack.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

Responsibilities:

Build and refine GenAI agents that interact with internal systems

Develop MCP tools and secure integrations

Create and maintain knowledge bases and retrieval pipelines

Implement agent evaluation frameworks and guardrails

Work across Azure, Snowflake, and Databricks to support production AI systems

Key Skills & Requirements:

NEEDS to be a team player and work well with others

Hands-on experience building and deploying GenAI agents (including open-source LLMs) in production environments

Strong knowledge of MCP, tool integrations, and agent orchestration

Proven ability to design and maintain knowledge bases, vector search, and retrieval systems independently

Rapid GenAI prototyping (vibe coding)

Cloud expertise: Azure (preferred), AWS, or GCP; secure, governed infrastructure

Expert-level SQL skills; experience with Snowflake (flexible)

Experience with Databricks for data, ML workflows, and predictive modeling

Solid background in traditional ML (classification, clustering, etc.)

Ability to build evals, guardrails, and safety layers for agents at scale

Experience with MLOps and LLM Observability

5+ years of relevant experience; independent and collaborative team player

Comfortable with LLMs and working in a team environment Azure, Databricks, and Snowflake expertise