Top Tech Jobs & Startup Jobs in Chicago, IL

Owns backend product features powering digital airport lounge experiences. Translates business epics into features and user stories, prioritizes roadmaps, defines acceptance criteria, validates solutions through data and research, and collaborates with technology, design, data science, strategy, marketing, and guest experience teams in an agile environment.

Owns A/B testing and optimization of credit card landing-page experiences. Partners with marketing to align performance strategy and conversion goals, while leading designers, engineers, business analysts, and legal partners in delivering personalized digital journeys. Applies customer-centered, business-focused, technology-driven, and transformational product management practices to create innovative consumer-facing products.

Build, deploy, scale, and maintain production machine learning models and platforms. Responsibilities include designing ML systems, developing data pipelines, operating distributed systems and cloud infrastructure, automating testing and deployment, monitoring models, applying responsible AI practices, and collaborating with product, data science, and engineering teams. The role requires advanced programming, machine learning, distributed computing, Kubernetes, and cloud experience.

Lead architecture and hands-on engineering for Capital One’s Settlement platform modernization in the cloud. Define technical vision, design scalable and reliable systems, guide migration from monoliths to microservices and event-driven platforms, establish API and coding standards, and oversee technical quality. Mentor engineers, conduct architectural reviews, contribute proof-of-concept work, influence cross-divisional initiatives, and advance security, DevOps, performance, and operational excellence.

Manages data governance and pricing-related risks by overseeing processes, controls, reporting, documentation, and improvement initiatives. The role analyzes process data, identifies gaps, resolves policy-related issues, collaborates on enterprise projects, represents departmental interests, and trains junior staff and internal stakeholders. Responsibilities include maintaining procedures and diagrams, recommending process changes, supporting executive reporting, and ensuring adherence to data management and governance frameworks.

Architect, build, and deploy enterprise-scale generative AI and autonomous agent systems for HR technology. Lead multi-agent workflows, full-stack cloud applications, distributed microservices, and technical initiatives while ensuring security, governance, compliance, and operational excellence. Partner with product managers, architects, and risk teams; establish engineering standards; mentor developers; evaluate emerging technologies; and reduce technical debt. The role requires expertise in programming, databases, APIs, cloud platforms, CI/CD, infrastructure as code, RAG, vector search, and LangChain or LangGraph.

Lead full-stack engineering initiatives and development teams building distributed, cloud-native systems and developer experience platforms. Design and implement reliable, high-performance microservices and full-stack solutions using modern programming languages, databases, containers, and cloud services. Provide architectural leadership, shape platform roadmaps, establish technical standards, mentor engineers, drive cross-functional initiatives, and apply observability and reliability practices at scale.

Leads complex full-stack engineering initiatives, technical projects, and developer teams. Designs and implements large-scale distributed, microservices, and cloud-native systems using modern programming languages, databases, containers, and cloud platforms. Provides architectural leadership, shapes platform roadmaps, establishes engineering standards, mentors engineers, drives reliability and observability practices, and collaborates with product and architecture leaders to deliver secure, high-performance solutions.

Build, deploy, scale, monitor, and maintain production machine learning models and infrastructure. The role involves developing ML components, optimizing algorithms and data pipelines, operating distributed systems and cloud-based platforms, automating testing and deployment, and applying responsible AI and model governance practices. Candidates collaborate with product, data science, and Agile engineering teams while using technologies such as Python, PyTorch, Spark, Kubernetes, and major cloud platforms.

Build and lead full-stack software engineering initiatives using cloud-based, distributed microservices and full-stack systems. Lead developers, define service boundaries and integration patterns, establish engineering standards, mentor team members, and deliver AWS solutions. Responsibilities include refactoring, reducing technical debt, improving performance, developing synchronous and asynchronous APIs, using modern programming languages and databases, and driving technical strategy across Agile teams.