Top AI Engineer Jobs in Chicago, IL

The Senior AI Engineer will design, develop, and implement multi-agent AI systems to optimize healthcare revenue management, focusing on agent orchestration and API integration.

The Applied AI Engineer role involves designing, building, and deploying AI-powered systems, collaborating with business teams, and measuring solution impact. Responsibilities include translating workflows into systems, driving outcomes, and ensuring regulatory compliance while fostering community sharing of learnings and tools.

The AI Engineer III is responsible for the reliability and scalability of AI solutions, managing CI/CD pipelines, observability, and ensuring security in deployments. They architect and maintain tools within Azure AI Foundry, collaborate with SRE teams, and optimize model performance while enforcing governance through automated controls.

The Senior AI Engineer will develop AI solutions for incident management, collaborate cross-functionally, and enhance observability tools through iteration and ownership.

The Senior AI Engineer will design and maintain customer-facing AI tools by building APIs, optimizing workflows, and conducting experiments with generative AI models, ensuring system reliability and integration with production systems.

Lead the buildout and scaling of AI capabilities at Optimal Dynamics, establishing engineering standards and delivering production systems. Own end-to-end initiatives from data readiness to production launch, collaborating cross-functionally and mentoring teammates.

The role involves developing AI-powered features, including agent capabilities, ensuring their reliability and scalability, and collaborating with cross-functional teams. Candidates should have strong hands-on experience with LLMs and Python in production environments.

Design, build, and operate production-grade AI and automation systems for GTM teams. Implement multi-agent architectures, integrate LLM APIs and marketing/CRM platforms, maintain CI/CD and reliability, enable stakeholders with docs and playbooks, and measure business impact through routing, analytics, and human-in-the-loop orchestration.

As a Staff AI Engineer, you'll own the architecture of AI pipelines, lead technical projects, mentor engineers, and influence product development in cybersecurity.

The Senior AI Engineer will create systems to manage cybersecurity alerts using AI, designing and implementing production pipelines and retrieval systems, while ensuring clear decision-making in security contexts.

As a Staff Backend AI Engineer, you will design and operate backend AI systems for Arbiter's care orchestration platform, ensuring reliability, low latency, and scalability while collaborating across teams and mentoring junior engineers.

The Full-Stack Applied AI Engineer will design and build AI-enabled products, own delivery from UI to backend, and implement robust systems with a focus on security and reliability, collaborating closely with clients and team members.

Lead technical vision and execution for enterprise-scale AI, automation, and data initiatives. Architect scalable, secure AI systems and data pipelines, mentor engineers, drive cross-functional alignment, and deliver high-impact production solutions that improve productivity and business outcomes.

The Staff AI Engineer will drive architecture and implementation of AI-assisted engineering practices, overseeing technical standards, automated testing, and code review systems for software development in a regulated fintech environment.

Responsible for designing and deploying AI solutions, developing ML models, collaborating with teams, ensuring model performance, and adhering to ethical guidelines.

Interns will create a RAG pipeline for the HCL Informix Database Server, configure tools in VSCode, and capture system performance metrics.

Lead AI safety strategies for autonomous vehicles, ensuring compliance with safety standards, mentoring teams, and guiding technical projects in AI/ML development for safety-critical applications.

As an AI Engineer, you will manage analytical projects, engage in causal modeling, feature engineering from data, and build AI-driven internal tools, partnering with various teams to develop customer solutions.

The AI Engineer - Marketing Operations will design, deploy, and manage AI systems to enhance marketing efficiency, integrate with CRM infrastructure, and optimize revenue impact through production-grade applications.

The Agentic AI Engineer is responsible for deploying, executing, and improving Machine Learning solutions, creating scalable systems, and collaborating with teams to drive strategy and business value through analytics.

The Senior AI Engineer will design and implement AWS-based AI solutions, build AI-powered features, ensure code quality, and collaborate across teams to enhance digital investigations.

Develop and deploy production-grade AI/ML models, design end-to-end pipelines, and ensure compliance while collaborating with stakeholders in a federal environment.

Develop AI solutions for marketing teams, integrating AI agents and workflows while coaching teams for self-sufficiency in AI use.

The Senior Applied AI Engineer will design and develop GenAI features for Teamworks' Hub product, focusing on production-grade systems and architectural decisions. Responsibilities include full ownership of features, collaborating with cross-functional teams, and establishing best practices for reliable AI systems.

As a Full Stack AI Engineer, you'll build AI applications and products, prototype solutions, and collaborate with founders in a fast-paced environment.