Data Scientist

Software Engineer

Location: Mount Prospect, IL, US, 60056 Business Unit: Atlas

The AI Engineer designs, develops, and deploys AI/ML-powered software solutions that advance Atlas's business operations and product innovation. Working within the software engineering team, this role builds and integrates AI capabilities—including LLM-based tools, copilots, data pipelines, and cloud applications—in alignment with established architecture, engineering standards, and product roadmaps. The ideal candidate combines hands-on technical depth across the full AI/ML lifecycle with strong collaboration skills, translating requirements from product and engineering leadership into scalable, reliable, production-grade solutions while upholding security, privacy, and responsible-AI practices.

Key Responsibilities

• Solution Development
• Deployment & MLOps
• Collaboration & Process
• Compliance & Quality

Requirements

Education: Bachelor's degree in Computer Science, Software Engineering, Data Science, Data Engineering, Electrical/Computer Engineering, or related field required. Master's degree preferred (AI/ML, Computer Science, Software Engineering, or related).

Experience: 2+ years in software engineering, architecture, or applied data/ML engineering roles, with experience delivering AI/ML solutions (model development and/or LLM/RAG applications) into production environments. Hands-on capability designing and building AI-powered applications, including rapid prototyping through production deployment.

Technical Skills: Experience with LLM-based applications (prompting patterns, tool/function calling, RAG, embeddings/vector databases, guardrails, and evaluation techniques). Experience with cloud platforms (Azure or AWS), APIs/microservices, CI/CD pipelines, and secure deployment practices. Strong software design and modular development skills; ability to contribute to scalable, maintainable architectures and follow established engineering standards. Working knowledge of data security, privacy, and responsible AI practices (access control, governance, auditability). Familiarity with software verification/validation, risk-based testing, and quality management practices in regulated or quality-managed environments.

Professional Skills: Able to complete assigned work with appropriate guidance while contributing effectively as a team player in a fast-paced, deadline-driven environment. Strong interpersonal and communication skills; able to collaborate effectively across engineering and cross-functional teams and contribute to technical documentation and design discussions. Strong prioritization and organizational skills; able to manage multiple tasks and deliver high-quality results.

Preferred / Nice-to-Have: Relevant certifications: Azure AI Engineer, AWS ML Specialty, Databricks, or equivalent. Understanding of embedded ML applications.

Compensation

Employee Type: Salaried Currency: USD Salary Minimum: 120,000 Salary Maximum: 140,000 Incentive: No