AI Engineer jobs in Chicago, IL

You will design and implement AI Quality Engineering strategies, including AI-native testing, validation processes, and runtime quality controls for enterprise AI solutions. The role involves collaborating with cross-functional teams to ensure the reliability, observability, and performance of AI-enabled healthcare workflows.

Develop and test full stack, cloud-native applications on AWS, translating client needs into solutions across architecture, design, implementation, and testing. Troubleshoot application and platform issues, apply AI-enabled engineering methods, collaborate with engineering teams, and review work while mentoring junior colleagues.

The Principal AI Engineer is responsible for designing, building, and operating shared AI platform capabilities and setting engineering standards for the organization. This role focuses on operationalizing responsible AI, ensuring cost efficiency, and mentoring senior engineers to scale AI development across business units.

You will build agent tooling and infrastructure to support quantitative research, simulation, and trading workflows. This involves developing and integrating new models, coding agents, and optimizing system performance for engineers and traders.

Provide senior technical leadership for Analytics Engineering, shaping data foundations, modeling standards, architecture, governance, quality, tooling, and developer experience. Build trusted canonical datasets, semantic layers, and AI-enabled analytical tools that support self-service analytics and improve decision-making across the company.

You will design, implement, and deploy scalable AI solutions while partnering with clients across various industries to address complex business challenges. Additionally, you will provide thought leadership in scientific communities and guide non-technical teams in software development best practices.

The Data Engineer will build and maintain low-level data pipelines using Databricks and Apache Spark while coordinating with onshore and offshore teams. They are also responsible for supporting deployment, post-production maintenance, and communicating project status to engagement managers.

The PSE Director is responsible for securing the technical close of complex Data Analytics and AI solutions to drive consulting practice growth. This includes scoping technical solutions, collaborating with sales and delivery teams, and providing coaching to sales associates.

Develop, implement, and integrate pre-trained AI models into healthcare applications using Python or C#. Collaborate with cross-functional teams to design scalable AI solutions that enhance operational efficiency and deliver measurable value.

Design and build production-grade conversational and Agentic AI applications using Python and modern software engineering practices. Integrate agents with enterprise APIs, databases, and contact-center platforms while ensuring secure authentication and observability.

Design and build production-grade conversational and Agentic AI applications using Python and modern software engineering practices. Integrate these agents with enterprise APIs, databases, and contact-center platforms while ensuring secure authentication and observability.

Design and build production-grade conversational and Agentic AI applications using Python and modern software engineering practices. Develop and integrate RAG solutions, enterprise-grounding, and agent orchestration while ensuring secure authentication and observability.

The role involves acting as the technical face of AvePoint to help enterprise customers implement AI trust, governance, and security solutions. Responsibilities include leading discovery workshops, scoping technical projects, and building prototypes and production-ready AI agents and pipelines.

You will architect and own the marketing data infrastructure, including ETL/ELT pipelines and Databricks models to power self-serve analytics and AI agents. Additionally, you will partner with cross-functional teams to define the technical roadmap and translate ambiguous business questions into scalable data products.

Drive technical wins for complex Cloud AI workloads by supporting the business cycle from evaluation through customer ramp. Provide deep technical consultation and develop prototypes to secure buy-in from customer domain experts.

Design, prototype, develop, and deploy domain-specific AI agents that collaborate with other agents to gather information, generate insights, and perform intelligent tasks. Partner with business, transformation, and AI platform teams to deliver scalable solutions, monitor and optimize production systems, and validate their reliability and performance.

The role involves designing and securing AI-enabled products and cloud environments using Zero Trust principles and secure software development lifecycles. You will collaborate with stakeholders to implement production-quality AI security architectures and automated threat management capabilities.

The engineer will design and implement secure architectures for generative and agentic AI, applying Zero Trust controls across cloud environments and development pipelines. They will also lead client discovery sessions and develop production-quality AI security platforms while mentoring team members.