Top Tech Jobs & Startup Jobs in Chicago, IL

The AI Solutions Lead will expand Quantiphi's business in key insurance accounts by managing executive relationships, developing account strategies, leading sales initiatives, and ensuring client satisfaction.

Design, develop, and deploy production forecasting models and agentic AI solutions on GCP. Perform EDA, feature engineering, experiment design, and model interpretability. Build and integrate AI agents (LangChain, Vertex AI Agents) into quotation and forecasting workflows, maintain MLOps pipelines (Vertex AI Pipelines, Cloud Composer), and present results to stakeholders.

The Sales Leader for Life Insurance is responsible for acquiring new customers, developing executive relationships, and driving sales of technology services to Life Insurance companies, focusing on AI and cloud solutions.

Lead per-SYSID assessments and design L2 sequence and data-flow diagrams. Define Kafka topic topology and microservice boundaries, plan Oracle AQ to Confluent Kafka migrations, assess Spring Boot migration paths, design AWS Step Functions for batch orchestration, and produce current vs. future-state architectures.

Architect and implement MLOps strategies, design ML pipelines, mentor teams, and ensure compliance on Google Cloud, focusing on AI/ML best practices.

Design and lead large-scale AWS migrations (rehost/replatform), architect cloud infrastructure and platforms, automate migrations with IaC and scripting, troubleshoot OS/database issues, and implement hybrid networking and security best practices.

Design and deliver enterprise-grade Generative AI solutions on AWS using Bedrock and AgentCore. Architect LLM-based applications, RAG pipelines, agentic workflows, vector DB integrations, and APIs. Optimize models for performance, cost, and quality, ensure security and governance, lead teams, and troubleshoot production GenAI systems.

Architect and implement enterprise-grade MLOps/LLMOps platforms on AWS and Kubernetes. Design ML/LLM pipelines for training, validation, deployment, monitoring, governance, CI/CD, and observability. Serve as technical authority, conduct architecture reviews, ensure security and compliance, and mentor engineering teams across projects.

Lead end-to-end delivery of enterprise Generative AI programs (LLMs, RAG, Agentic AI). Define roadmaps, manage multi-workstream global teams, align technical delivery with business outcomes, guide architecture, MLOps, GPU/inference optimization, vector DB and fine-tuning strategies, ensure AI governance, and maintain executive stakeholder relationships.

The AI Engineer will build AI-driven workflows, integrating customer requirements into scalable solutions while managing both front-end and back-end elements in a cloud environment.