Top AI Engineer Jobs in Chicago, IL

The ERP AI Engineer - Manager at PwC leads teams in AI/ML engineering, manages client relationships, and designs AI solutions, all while mentoring team members and addressing complex business challenges.

The AI Engineer Manager leads the Data and Analytics Engineering team in developing AI solutions, manages client accounts, analyzes data, and fosters team leadership and relationships with clients.

Rapidly prototype and validate AI solutions for advisor workflows: integrate models, signals, and UX into experiments, test feasibility and performance, iterate with user feedback, document technical learnings, and hand off prototypes for productionization.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

As a GTM AI Engineer, design and execute AI-driven workflows for Superhuman's go-to-market stack, improving automation in sales processes and team collaboration.

Design, build, and ship production-grade agentic AI workflows using LangGraph, Temporal, and Pydantic. Implement AI observability with LangFuse, set AI engineering standards (RAG, prompt management, tool-calling), benchmark LLMs, deploy cloud AI (containerization, cost management), and mentor engineers while supporting enterprise SLA, security, and compliance needs.

This role involves defining AI architecture, improving system quality, leading teams, and building production-ready AI systems at Drata.

As an AI Engineer, you will build and scale AI business applications, focusing on generative AI. Responsibilities include rapid prototyping, applying software engineering best practices, and providing production support.

The AI Engineer role involves prototyping AI solutions, collaborating with cross-functional teams, validating workflows, and documenting technical learnings.

The Senior AI Engineer will lead AI adoption, experiment with solutions, package workflows, measure impact, and drive collaboration in engineering.

As a Principal AI Engineer, you'll design production-grade systems integrating generative AI in mental healthcare, overseeing architecture and applied research.

Lead the development of innovative AI solutions, guide teams through complex challenges, and collaborate with diverse stakeholders to enhance operational effectiveness and achieve strategic objectives.

As a Senior Associate in Audit and Assurance, you'll evaluate AI solutions, manage AI/ML controls, and enhance transparency in reporting. Responsibilities include data analysis for governance strategies, guiding compliance practices, and contributing to innovative thought leadership in AI governance.

Lead the design and implementation of enterprise AI/ML solutions, oversee project performance, mentor leaders, and ensure compliance with Responsible AI.

The role involves designing and implementing AI/ML solutions, leading teams, mentoring staff, and managing project delivery while ensuring client satisfaction.

As a Senior AI Engineer, you'll design and implement AI-driven solutions, focusing on full-stack development and production-grade applications while mentoring junior team members.

The Applied AI Developer will design and develop AI applications, build infrastructure for agentic AI systems, integrate APIs, and collaborate with stakeholders on AI solutions.

Design and implement AI capabilities, transition prototypes to production, build agent workflows, optimize data retrieval, and automate evaluation processes.

Lead the design and delivery of scalable voice and chat solutions using Amazon Connect, focusing on integrations, reliability, and performance optimization.

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 Principal AI Engineer will lead technical architecture and strategy within the Simplification CoE, driving scalable AI solutions and mentoring teams.

Build and deploy transformer and sequential deep learning models using large-scale financial and behavioral data to power personalized growth and marketing experiences. Work cross-functionally to design scalable training, serving, and monitoring infrastructure (batch and real-time), contribute to experimentation and optimization frameworks, and maintain production-grade MLOps systems to improve member engagement and business metrics.

Lead the design, build, and ownership of production AI workflow and integration infrastructure enabling non-engineers to configure multi-step LLM-driven automations. Architect connectors, orchestration, security, CI/CD, monitoring, and bidirectional write-back while partnering with stakeholders and enforcing governance and compliance.

Build and maintain integrations and multi-step automated workflows between the enterprise AI platform and operational tools. Implement and sustain write-back logic, troubleshoot integration issues, ensure production reliability and security, support non-technical practitioners, participate in reviews, and contribute to monitoring, documentation, and training.

The role involves designing AI systems for mental healthcare, focusing on building scalable, production-grade systems that enhance patient engagement and clinical operations. Responsibilities include setting technical standards and ensuring safety and reliability while working with advanced AI technologies.