Top AI Jobs in Chicago, IL

Lead ownership of reliability, evaluation, and safety for an AI copilot in a trading platform. Build eval systems, benchmarks, automated quality gates, monitoring, and model improvement loops; partner with engineering and product to define safe tool contracts and ensure predictable, auditable assistant behavior in trading workflows.

Lead and grow an AI Platform Enablement team to build a governed internal AI development environment. Define platform strategy, partner with security and infrastructure, drive adoption via enablement programs, and establish metrics for usage, onboarding, and control effectiveness. Act as an executive-facing leader delivering secure, scalable platforms and change management.

Lead end-to-end product development of enterprise-grade AI-powered healthcare solutions (generative AI, LLMs, RAG, automation). Drive roadmap, customer validation, cross-functional execution, measurable adoption, and business outcomes while mentoring product practices.

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.

Lead the architecture and technical vision for AI-powered GTM systems, defining patterns for low-code and custom agentic pipelines. Build reference architectures, design multi-system integrations and RAG/LLM orchestration, evaluate AI tools, drive governance and observability, and partner with GTM leadership to deliver production-grade, scalable solutions.

Lead strategy and technical direction for generative and multimodal vision systems. Build end-to-end model workflows, improve realism, controllability, and robustness, drive evaluation and production-readiness, partner with engineering to deploy optimized inference, and mentor scientists while owning a major technical pillar from research to production.

Lead product vision and strategy for an end-to-end AI-powered software factory. Integrate planning, coding, review, and verification across GitLab Duo Agent Platform and product areas. Collaborate with engineering, design, and GTM teams, identify gaps and dependencies, present recommendations to executives, and drive execution to deliver cohesive developer workflows.

As a Software Engineer, you will build AI systems to enhance developer workflows, implementing agents and servers, and ensuring code reliability through evaluation pipelines.

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.

Embed with functional teams to discover high-value workflows, build and ship AI agents and automations on shared infrastructure, coach teams to self-sufficiency, monitor adoption and quality, productize durable agents into the platform, and document reusable playbooks to scale transformation across the company.

Lead distributed engineering teams to build and operate real-time data serving, LLM orchestration, and ML pipeline infrastructure powering low-latency, personalized connected-home experiences. Own delivery, reliability, observability, drift detection, and model rollout; manage sprint cadence, hiring, and technical coaching while coordinating with product, architecture, AI/ML ops, and video intelligence teams.

Lead design and deliver SAP BTP AI solutions for Finance. Partner with SAP Finance teams to identify AI use cases, build GenAI capabilities (RAG, Joule Skills, agents), ensure secure, scalable integrations, validate feasibility via POCs, and produce production-ready solutions for reconciliations, controls, reporting, and financial close.

Lead product for AI Corps: define roadmap, metrics, and platform powering fellow recruitment, matching, deployment, and enterprise L&D. Partner with Earned Revenue, Curriculum, Engineering, and Anthropic to run discovery, experiments, and ship high-quality experiences that scale to enterprise customers.

Lead client engagements to assess business challenges, define enterprise data and AI strategies, develop roadmaps, guide solution design and delivery, provide technical leadership and mentoring, and support practice growth via presales and thought leadership.

The Director of AI Engineering will develop AI-driven solutions, enhance trading workflows, oversee LLMs, and lead AI integration efforts.

The Machine Learning Scientist will develop AI frameworks for predictive modeling in oncology, collaborating with teams to enhance drug R&D efforts through advanced machine learning techniques and multimodal data integration.

Build and iterate fast AI prototypes for advisor workflows, integrating models, signals, APIs, and UX. Test feasibility and performance, capture technical learnings, and produce handoff documentation for production teams.

Rapidly prototype AI solutions embedded in advisor workflows: integrate models, signals, APIs and UX into experiments, validate feasibility and performance, and hand off documentation to production teams.

Lead design and launch of a tiered AI partner marketing program. Execute co-marketing, sales enablement, in-platform brand governance, attribution and reporting, client education, and cross-functional operations to drive partner-sourced pipeline and $1M closed-won revenue in year one.

Provide legal guidance on Rubrik's AI use and products, ensuring compliance with laws and contracts, drafting and negotiating AI terms, coordinating generative AI review processes, educating employees, and improving AI review controls and workflows across cross-functional teams.

Design and scale a reusable Customer Success AI platform: build foundational AI infrastructure (orchestration, memory, context, workflow engines), optimize model routing, observability, governance, and security, lead architecture and standards, mentor engineers, and partner cross-functionally to deliver enterprise-grade, multi-product AI capabilities.

Define vision, strategy, and roadmap for Customer Success AI products. Identify high-impact AI opportunities across workflows, manage products end-to-end from incubation to scale, partner cross-functionally, and drive adoption, measurement, and lifecycle optimization for AI-native employee productivity and operational intelligence.

Lead AI strategy for Payments Sales by translating sales priorities into scalable GenAI and data-driven products, driving adoption, partnering with product/data teams, ensuring governance, and enabling sales through training and cross-functional coordination to improve productivity and revenue outcomes.

Develop and operationalize ML and deep learning solutions (especially NLP/LLMs) for Wholesale Lending. Design experiments, build batch and real-time prediction pipelines and end-to-end AutoML/AutoNLP workflows, collaborate with product, data, engineering, legal and compliance teams, and deploy models to production on AWS.

Lead end-to-end development, deployment, and monitoring of ML and AI models for consumer finance products. Translate business needs into analytical plans, ensure governance and regulatory compliance, advise stakeholders, and mentor junior modelers.