Top Tech Jobs & Startup Jobs in Chicago, IL

The Senior Site Reliability Engineer improves the reliability, resilience, scalability, observability, and operational health of production services. Responsibilities include defining SLIs and SLOs, enhancing monitoring and incident response, automating infrastructure and deployments, reducing operational toil, troubleshooting distributed systems, and partnering with software engineering teams. The role owns reliability outcomes across multiple services, influences engineering practices, mentors colleagues, and drives continuous improvement across cloud platforms, CI/CD, infrastructure, and operational readiness.

Leads client-facing product implementations and merchant integrations, overseeing delivery standards, quality assurance, timelines, readiness reviews, and launch decisions. Serves as the subject matter expert for mobile checkout and app-based implementations, advises partners on integration approaches, and mentors implementation teams. Coordinates Product, Engineering, Design, and Operations while developing scalable playbooks, documentation, training, and best practices to improve onboarding, user experience, and platform adoption.

Leads client-facing implementation delivery for Early Warning Services products, guiding integrations, quality standards, timelines, technical and UX reviews, readiness assessments, and launch decisions. Serves as the subject matter expert for mobile checkout and app-based implementations, mentors team members, manages vendors and consultants, and collaborates with Product, Engineering, Design, and Operations. Develops scalable implementation playbooks, improves user experience and performance, and shares integration feedback to influence product roadmaps.

Manages fraud risk platforms, models, rules, vendors, and system performance. Develops platform requirements and recommendations, coordinates risk services roadmaps with Product and Technology, tunes systems with Fraud Operations, evaluates vendor technologies, and reports on risk performance. Leads cross-functional risk strategy initiatives with autonomy while supporting the protection of systems, data, and financial transactions.

Designs, builds, and operates infrastructure-as-code capabilities using Terraform and Ansible across cloud and on-premises environments. Develops reusable modules, policy-as-code guardrails, testing frameworks, secure credential patterns, configuration automation, and developer self-service tooling. Partners with security, compliance, platform, network, and CI/CD teams to implement controlled infrastructure changes, automate evidence collection, manage drift, and improve reliability. The role also mentors engineers, documents architecture, and leads complex technical initiatives.

Design, build, and operate a production AIOps agent platform for event observation, diagnosis, recommendations, and controlled automated actions. Develop agent runtimes, tool interfaces, event routing, telemetry, auditability, evaluation systems, feedback mechanisms, and operator experiences. Establish safety guardrails, approvals, permissions, rollback controls, and reliability standards. Collaborate across engineering, operations, security, risk, and compliance to deliver scalable, explainable, and regulated production capabilities.

Responsible for the development, testing, and deployment of complex solutions, collaborating with multiple teams and overseeing technical strategies and architecture. Lead engineering efforts, mentor engineers, and improve engineering standards.

Lead architecture and implementation of platform and data infrastructure; define technical strategy and roadmaps; build, automate, and document platform solutions; lead cross-functional projects, mentor junior engineers, ensure CI/CD, containerization, IaC and cloud best practices, and support risk management and compliance.

The Senior ML Operations Engineer is responsible for building and maintaining ML infrastructure, model deployment processes, and collaboration with data teams to optimize predictive modeling solutions.

Drive vision, roadmap, and delivery of internal enterprise data platform capabilities. Define self-service workflows for data ingestion, curation, governance, metadata, observability, data quality, and access. Collaborate with engineering, analytics, architecture, governance, and security to translate user needs into scalable product requirements, measure adoption and performance, and ensure platform reliability, compliance, and developer productivity.