Top AI Specialist Jobs in Chicago, IL

The AI Engineering Specialist will oversee project tasks, manage expectations, mentor junior members, and design scalable AI systems while working with advanced AI models and ML pipelines.

Design, build, test, deploy, monitor, and maintain production LLM-based agentic solutions for Commercial Customer Success. Integrate agents with CRMs and Samsara systems, define evaluation frameworks and success metrics, implement automated tests and monitoring, iterate on models and prompts, and demonstrate impact on customer outcomes and retention.

As a Curriculum Specialist, you will maintain and enhance computer science curriculum, create instructional materials, and support teachers while ensuring quality and alignment with standards.

Maintain and support enterprise AI tool environments; develop AI-powered scripts and small tools; provide escalated support and training; manage licensing, access, analytics, and compliance; collaborate with security and leadership to standardize and deploy AI processes firm-wide.

Support the Intelligent Process Automation Lab by managing business relationships, consolidating demand, prioritizing automation use cases, shaping portfolio strategy and roadmap, expanding RPA/AI PODs, enforcing discovery best practices and governance, and coordinating requirements and delivery with development teams.

Develop, support, and maintain automations on UiPath and Azure AI/Foundry. Serve as a technical lead translating business requirements into scalable automation solutions, optimize system performance, create/design prototypes and SDDs, collaborate with stakeholders, and participate in on-call support rotations.

The AI Adoption Specialist guides organizations in integrating AI technologies, developing strategies, conducting pilots, and overseeing deployment while monitoring performance.

Design, build, and operate a secure, scalable Generative AI platform on AWS (including Bedrock) to support production LLM applications in regulated financial environments. Own platform lifecycle: architecture, deployment, operations, monitoring, incident management, reliability, and performance. Implement LLM inference, RAG, Agents, guardrails, observability, security controls, access management, compliance, and cost optimization. Provide production support, reliability engineering, and AI governance.

Annotate tax forms by researching layouts, drawing precise bounding boxes, defining field schemas and relationships in Label Studio, exporting JSON/YAML, validating overlays, and documenting metadata and formulas for downstream model training.

Define and maintain benchmark datasets and gold standards, create training and certification materials, monitor annotator drift, perform double-blind quality audits, and act as a high-trust annotator for critical production labeling. Collaborate with Computer Vision and Data Ops to improve the quality pipeline and scoring models.

Design, build, and operate a secure, scalable Generative AI platform on AWS (Bedrock) for production LLM applications in regulated environments. Own architecture, deployment, monitoring, incident management, reliability, governance, cost optimization, and AI evaluation/Responsible AI practices.

Join an internal AI enablement team to assess workflows, build prompt-based automations and lightweight apps, coach business teams, test and document tools, track user skill development, research AI platforms, and ensure governance and security compliance.

The role involves designing and implementing automation systems, improving workflows, and developing tools for sales support using AI and automation platforms.

Embed with business teams to design and build AI-powered tools, automations, and workflows; coach and enable staff; create reusable solutions, documentation, adoption metrics, and governance; mentor junior members and translate AI developments into practical enterprise applications.

The AI Development Specialist engages with enterprise developer teams to sell coding assistants and AI solutions, co-sells with NVIDIA, and proposes consulting engagements, focusing on improving developer productivity and application performance.

Develop and optimize prompts, context management, and multimodal prompting workflows for LLM-powered products. Collaborate with Customer Success to iterate on prompts, review conversations and feedback, document and teach prompting best practices, and build small prototypes using Python and low-code tools to test complex prompting and data workflows.

Develop, test, and maintain applications using Java, Python, or Node.js. Write clean, efficient code, debug and optimize, collaborate with cross-functional teams, use data structures/algorithms, work with SQL/NoSQL databases, participate in code reviews, and stay current on AI/ML concepts, agents, and automation tools.

Lead discovery and build AI-enabled operational workflows across R&D and business functions. Translate requirements into practical solutions, own design-to-launch, optimize adoption, and manage Marketing Operations (campaigns, automation, tech stack). Measure outcomes, document solutions, and ensure alignment with shared AI standards.

The SAP AI Specialist will integrate AI within SAP systems, optimizing capabilities using SAP Joule and BTP AI services, and developing predictive analytics and automation solutions.

Design and build AI- and automation-driven solutions to accelerate Mortgage Cadence Platform configuration using LLMs and workflow automation. Develop integrations with system APIs, partner with implementation teams, create documentation and training, and propose new tools to improve implementation accuracy and scale.

Administer and maintain AI/ML and HPC testbed infrastructure: install and manage Linux systems, configuration management, version control, scripting, datacenter hardware operations, networking support, documentation, and collaborate with researchers and operations teams to ensure testbed availability and sustainability.

Lead change management for AI-powered tools and workflows: assess impacts, build adoption plans, create training and communications, coach leaders and enablement teams, recruit change champions, track adoption metrics, and share learnings across the Change Management team.

Provide insurance subject-matter expertise to improve generative AI models: design insurance tasks, create reference solutions, evaluate AI outputs with structured rubrics, refine scoring guidelines, and collaborate with research and engineering teams to produce high-quality training and evaluation data. Commitment of 35+ hours/week and proven senior insurance experience required.

Design and run red-team evaluations to find failure modes and edge cases in frontier LLMs. Create reproducible, multi-step benchmark tasks, document technical findings, and collaborate with researchers to refine grading and improve model robustness. Commit ~35 hours/week as a remote independent contractor.

Evaluate and improve LLM financial reasoning by designing real-world finance tasks, creating reference solutions, scoring AI outputs with structured rubrics, refining evaluation frameworks, and collaborating with researchers to raise data quality and model performance. Must provide detailed feedback and identify gaps to enhance AI across finance use cases.