QUALIFICATIONS

• Bachelor’s degree in Computer Science, Data Science, or a related field (or equivalent experience)
• 4+ years of experience in data engineering, machine learning, or related roles
• Strong proficiency in Python, including common AI/ML and data libraries (e.g., Pandas, PyTorch, Scikit-learn)
• Experience with cloud-based data architectures (e.g., lakehouses, data lakes, warehouses)
• Solid understanding of containerization (e.g., Docker) and version control (e.g., Git)
• Experience deploying AI services via REST APIs or microservices
• Familiarity with vector databases, LLMs, or Retrieval-Augmented Generation (RAG) systems
• Knowledge of orchestration tools like Airflow, Dagster, or Prefect
• Experience with client-facing consulting or cross-functional collaboration
• Excellent communication and problem-solving skills
• Legally authorized to work in the US without sponsorship
• Must demonstrate a “can-do” attitude
  We focus on candidates that display our “ACE” factor – Attitude, Compassion, and Enthusiasm to deliver quality solutions with exceptional customer service.

ABOUT US:

Sentinel delivers solutions that can efficiently address a range of IT needs – from security, to communications, to systems & networks, to software applications, to cloud and managed services; all of which include our staffing solutions for our clients. Since 1982, Sentinel has grown from providing technology maintenance services to our current standing as one of the leading IT services and solutions provider in the US. We have aligned with many of today’s global technology leaders including Cisco, Dell, VMware and Microsoft. Sentinel services customers both nationally and internationally with primary support operating centers in Downers Grove (HQ), Chicago, and Springfield, IL; Phoenix, AZ.; Lansing, and Grand Rapids, MI; Milwaukee, WI; and Denver, CO.
If you are MOTIVATED… you can make IT happen at Sentinel. Our commitment to our employees is to create a work environment that encourages creativity, an entrepreneurial spirit, fosters growth through certification and hands-on training, and values a team-oriented culture with rewards based on impact!
If you share our passion about what technology can do and want to be part of a top workplace environment – we’d like to have you join our team. Learn more at www.sentinel.com/careers.
As part of Sentinel’s employment process, candidates will be required to complete a background check. Only those who meet the minimum requirements will be contacted. No phone calls please.
Sentinel is proud to be an equal opportunity employer including disability and veterans. In accordance with Title VII and state regulations, all qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, marital status, pregnancy, genetics, disability, military, veteran status or any other basis protected by law.
If you are an individual with a disability and need assistance in applying for a position, please contact SentinelHR1@sentinel.com

RESPONSIBILITIES

The AI and Data Engineer will design and build scalable data pipelines, develop AI-powered applications and services (primarily in Python), and contribute to the delivery of advanced data and machine learning solutions. This role combines strong software engineering skills with practical experience in data platforms and applied AI, supporting both internal use cases and client-facing projects. This is a full time opportunity based in the United States where remote work is available with occasional onsite reporting to our Chicagoland, IL offices.

KEY RESPONSIBILITIES:

• Design, develop, and maintain data pipelines and modern data platforms (e.g., lakehouses)
• Build scalable AI services and applications using Python and related frameworks
• Collaborate with cross-functional teams to deliver end-to-end AI and data solutions
• Serve as a technical expert and advisor to internal stakeholders and external clients
• Ensure best practices in data governance, model reproducibility, and MLOps
• Contribute to the development of internal tools, templates, and reusable components
• Stay current with advancements in AI, data engineering, and cloud technologies