Engineering

Artificial Intelligence Engineering

New York Technology PartnersChicago, IL🇺🇸United StatesPosted Sep 23, 2026

Quick Overview

Seniority

Mid Senior

Work mode

On Site

Location

Chicago, IL, United States

Posted

6 days ago

Jira

Job Description

We are launching a high-visibility, greenfield initiative designed to transform how our organization leverages internal corporate data. We are seeking a pragmatic, collaborative technologist to lead the effort in making our internal systems data (e.g., ServiceNow, JIRA, and other enterprise platforms) highly consumable and actionable for Large Language Models (LLMs) and agentic AI systems.

This role is ideal for a professional with a strong foundation in Data Engineering, Data Science, or Data Analytics who has practical experience bridging the gap between robust data pipelines and applied AI. You will not be expected to be an AI research scientist; rather, you will be the crucial link that ensures our data is structured, reliable, and ready for modern AI tools (such as Anthropic s Claude).

Primary Duties and Responsibilities

End-to-End Delivery: Own the design, development, and deployment of data pipelines and infrastructure that feed internal corporate data into LLM-powered applications and agentic workflows.
Data Architecture: Architect and implement data warehousing, data modeling, and pipeline solutions to ensure high-quality, reliable data consumption by AI models.
Applied AI Integration: Collaborate on the integration of AI models into internal business processes, ensuring practical, scalable, and secure implementations.
Mentorship & Leadership: Actively mentor and elevate a team of early-career engineers (including entry level candidates), providing guidance on code quality, architecture, and professional development without formal supervisory authority.
Risk & Governance: Implement practical technical safeguards against AI-specific risks, including output validation, data privacy, and hallucination mitigation, in alignment with corporate governance standards.
Cross-Functional Collaboration: Partner closely with stakeholders across the organization in this greenfield environment, requiring exceptional communication skills and a highly collaborative mindset.

Qualifications and Technical Skills

Experience: 4 to 6 years of professional experience in Data Engineering, Data Science, Data Analytics, or a closely related technical field.
Core Technical Stack: Strong, demonstrable proficiency in Python and SQL.
Data Engineering Fundamentals: Solid experience building and maintaining data pipelines, data modeling, and data warehousing solutions.
Applied AI Experience: Hands-on experience building, integrating, or working with LLM-powered applications or agentic systems. Direct experience with Anthropic s Claude is highly preferred, but practical experience with any major AI/LLM tool is acceptable.
Infrastructure: Working knowledge of cloud infrastructure (AWS preferred), along with comfort in Docker, CI/CD, and containerization fundamentals.
Leadership: Proven track record of mentoring junior engineers and fostering a collaborative team environment.
Education: Bachelor s degree in Computer Science, Engineering, Data Science, or a related technical field (Master s degree is a plus).