1108 Software Engineer Studio Java Ai jobs in Chicago,IL

Ulta Beauty

Bolingbrook, IL 60440

8+ years of progressive experience in software engineering, AI engineering, or ML systems development, including leadership in enterprise-scale environments.
Hands-on experience delivering production-grade AI/ML systems from development through deployment and monitoring.
Strong expertise in cloud-native environments (GCP, Azure, AWS) and modern AI system integration patterns.
Experience working in cross-functional delivery models with embedded engineering teams.
Proven ability to influence without direct authority across technical and domain teams.
Exposure to responsible AI principles and tooling including fairness testing, explainability techniques, and model risk governance.
Experience with LLM-based architectures, RAG systems, and generative AI evaluation frameworks.
Demonstrated experience establishing engineering standards, governance frameworks, and quality controls across multiple concurrent initiatives.

Unavailable

Chicago, IL 60629

Aramco

Chicago, IL 60290

Bachelor's or Master's degree in Computer Science, Computer Engineering, Information Systems, or a related field.
Minimum of 15 years in IT, with at least 4 years in a Solution Architect or Lead Data Engineer role.
Proven track record of delivering at least two large-scale enterprise data platform migrations or greenfield builds.

Guidehouse Careers

Chicago, IL 60629

Ulta Beauty

Bolingbrook, IL 60440

Master's degree in Computer Science, Data Science, AI/ML, or equivalent professional experience is required.
12+ years of experience in software engineering and systems architecture, with at least 5+ years specifically focused on leading large-scale AI production environments.
Experience managing other architects or technical leads (Data Scientists) and overseeing multiple simultaneous workstreams/pods.
Deep expertise in the modern AI stack, including LLM orchestration (LangChain, LlamaIndex), vector databases (Pinecone, Milvus), and traditional ML frameworks (TensorFlow, Scikit-Learn).
Hands-on experience designing agentic systems, autonomous workflows, or cognitive architectures
Strong understanding of Platform Architecture and MLOps, including Kubernetes, model serving (BentoML, TGI, vLLM), and automated retraining pipelines.
Experience, working with and influencing, Enterprise Architecture frameworks and navigating complex governance, risk, and compliance (GRC) environments.
Hands-on experience with one or more cloud computing platforms (e.g. Google Cloud, Azure, AWS)
Exceptional verbal and written communication skills, with the ability to create clear architectural diagrams and whitepapers for both technical and non-technical audiences. Comfort and experience presenting and compiling materials for Executive audiences.
Stay current with emerging AI technologies and methodologies, evaluating their potential application