Top Tech Jobs & Startup Jobs in Chicago, IL

The Physician Editor (Obstetrics-Gynecology) reviews and edits clinical content, updates literature, and collaborates with experts to ensure clinical relevance and accuracy in medical information.

The Product Management Associate Director will lead the strategic vision for a customer-facing platform, managing product lifecycle and delivering modern, AI-enabled customer experiences while enhancing integration with other systems.

The Industry Solutions Consultant will ensure compliance and functionality in DB plan software, collaborating with teams for testing and improvements.

The Managing Counsel will provide legal guidance on contracts, oversee the legal support of business lines, and manage an attorney. Requires substantial experience in corporate law, particularly in SaaS and software transactions.

The Lead Application & Product Architect will design and drive architecture for tax services, review code, lead modernization efforts, ensure security compliance, and communicate design tradeoffs to technical and leadership teams.

The Business Analysis Manager drives operational excellence through continuous improvement, data analysis, and cross-functional collaboration, enhancing efficiency and productivity in service operations.

Design and implement full-stack applications and AI agents to enable rapid development and deployment of AI solutions in critical industries. Mentor engineers and take ownership of projects while applying secure SDLC practices and collaborating with cross-functional teams.

The Lead AI Solutions Architect will develop and validate Generative AI solutions, mentor teams, and collaborate with product stakeholders. Responsibilities include architectural guidance and prototype development.

The Lead Technical Writer is responsible for creating and maintaining complex clinical content, conducting data analysis, leading projects, and communicating with stakeholders to enhance product visibility and quality.

Lead ownership of Terraform-based Azure infrastructure for AI products, design scalable PaaS architectures, build observability and SLO-driven dashboards, enable developer self-service with CI/CD and templates, and coordinate cloud decisions with enterprise infrastructure and product teams.