Software engineer jobs in Chicago, IL

About the role

We're looking for a seasoned Staff Platform Engineer who can own the full stack of infrastructure concerns — from bare metal and virtualization layers up through container orchestration, observability, and CI/CD pipelines. You'll work closely with software engineering, security, data operations, and client connectivity teams. You'll also serve as a senior escalation point for complex infrastructure and platform issues — including those that touch financial data feeds, custody integrations, and low-latency market data ingestion. Experience operating in a regulated financial environment is a meaningful advantage here.

What you'll bring

• 7+ years of experience in platform engineering, Linux systems administration, or DevOps/SRE roles — with at least 3 years in a financial services or FinTech environment.
• Deep, hands-on expertise with RHEL and Debian-based Linux distributions
• strong command-line proficiency and systems-level diagnostic ability.
• Production-grade experience with Kubernetes (cluster operations, Helm, RBAC, networking, storage)
• Proven infrastructure automation experience using Ansible, Salt, Terraform, or equivalent IaC tooling — not just writing playbooks, but designing automation frameworks.
• Solid experience with CI/CD platforms (GitLab CI, Jenkins, GitHub Actions, Spinnaker) and software delivery pipeline design.
• Hands-on experience with observability stacks: Prometheus, Grafana, Elastic Stack (ELK/EFK), or equivalent enterprise monitoring and log aggregation tooling.
• Strong working knowledge of Java applications and JVM internals — tuning, GC analysis, heap profiling — given the prevalence of Java-based financial platform services.
• Familiarity with financial data connectivity concepts: FIX protocol, SWIFT messaging, SFTP/FTPS-based file transfer workflows, market data feed management (Bloomberg, Refinitiv, etc.), and custodian data integration patterns.
• Working knowledge of relational database systems (MySQL, PostgreSQL) and non-relational/time-series data stores in the context of financial data platforms.
• Strong networking fundamentals: TCP/IP, DNS, TLS/PKI, load balancing, VPN/MPLS, firewall policy — especially as applied to host-based and data center environments.
• Demonstrated comfort and fluency with AI-assisted workflows — actively leverages AI tools (e.g., Claude or equivalent) to accelerate troubleshooting, automate documentation, generate and review infrastructure-as-code, and augment engineering output

Benefits