Top Tech Jobs & Startup Jobs in Chicago, IL

Build and maintain scalable cloud-native ETL/ELT pipelines and data platforms to support analytics and ML. Implement IaC and CI/CD, enable MLOps, ensure data quality, monitoring, and collaborate with data scientists and product teams to deploy production AI services.

Design, build, and operate enterprise AI/ML platform capabilities (AIOps/MLOps/LLMOps). Develop GenAI features, experiment with models and services, and architect end-to-end solutions. Collaborate with data, cloud, and business teams, drive engineering execution, promote best practices, and mentor engineers. Ensure platform reliability, monitoring, and scalable deployments across cloud environments.

Lead and coach a team of Senior Client Relationship Managers serving national accounts. Drive growth, renewals, stewardship, cross-functional collaboration, escalation resolution, performance tracking, licensing compliance, and continuous improvement to deliver exceptional client experiences.

Design, build, and maintain scalable data assets and pipelines for analytics and ML; validate and ingest diverse data sources; perform exploratory data analysis and data quality checks; collaborate with cross-functional teams and produce reproducible code and documentation.

The Senior IT Engineer will lead full stack development projects focused on AWS, architecting APIs, mentoring junior engineers, and ensuring application performance and security.

Design and build production-scale data pipelines, orchestration, and integrations on GCP to enable metadata-driven governance, lineage, automation, and AI-enabled workflows. Implement secure, observable, cost-efficient cloud data solutions, embed governance into engineering workflows, and drive CI/CD, testing, monitoring, and platform engineering best practices.

Manage multinational network partner relationships and service delivery to meet KPIs. Lead stewardship meetings and in-person visits, handle escalations, support onboarding, maintain Global Online portal and mailbox, perform SLA reporting, assist with outbound reinsurance slips, premium reconciliation, and local policy quality control.

Lead alignment of Enterprise Data Services or Applied AI & Analytics portfolios with enterprise data/AI strategy. Oversee portfolio prioritization, IT budgeting, financial accountability, vendor management, and value-stream coordination. Partner with executive stakeholders to meet efficiency targets and manage annual portfolio spend (~$90M+). Promote Agile/DevOps/Scaled Agile practices and continuous improvement.

Design, build, and operationalize production-grade AI/Machine Learning solutions and MLOps services. Deploy models and API services to AWS and GCP using CI/CD and IaC, implement workflow automation, monitor post-production performance, research generative/ML techniques, and mentor junior engineers while collaborating with cross-functional data, cloud, and architecture teams.

Lead Applied AI strategy and execution across Employee Benefits and Operations, overseeing ML, generative and agentic AI, RAG, and predictive analytics lifecycles. Drive governance, model risk management, evaluation, deployment, cross-LOB prioritization, talent architecture, and regulatory readiness to improve enrollment, billing, service, and operational efficiency.