3 days ago
Base Salary
$126k - $210k/yr
Responsibilities
- Lead the architecture, design, development, deployment, and maintenance of high-volume, low-latency Java applications on Google Cloud Platform.
- Lead the transition to agentic software engineering by standardizing toolchains, prompts, context repositories, and agentic workflows.
- Build and maintain shared agent infrastructure, including repository context, MCP server integrations, codebase indexing pipelines, and local developer tooling.
- Design evaluation harnesses, automated tests, static analysis, and CI/CD guardrails for validating AI-generated code and identifying concurrency, memory, security, and performance issues.
- Maintain high-throughput CI/CD automation and support reliable, secure production delivery.
- Drive architecture decisions across team boundaries and contribute to engineering tooling and culture initiatives.
- Mentor engineers through workshops, code reviews, design reviews, pairing, and hands-on training in AI-native engineering.
- Operate under pressure and participate in on-call responsibilities for systems with financial and regulatory impact.
Requirements
- Bachelor’s degree or higher in Computer Science, Mathematics, Financial Engineering, or a related field.
- At least 8 years of hands-on experience building, deploying, and maintaining scalable real-time systems across the full stack.
- Expert-level Java and Spring experience, including multithreaded and concurrent applications, lock-free data structures, memory management, thread pools, and race-condition diagnostics.
- Production experience with AI coding agents such as Gemini CLI, Claude Code, and Codex, including multi-step tasks, agent-authored pull requests, and agent-driven test generation.
- Deep experience with Google Cloud Platform services including GKE, Pub/Sub, BigQuery, Cloud Run, and Dataflow.
- Experience with real-time messaging and stream-processing technologies including Kafka, MQ, and Flink.
- Strong SQL, Postgres, and Python proficiency for scripting, evaluations, data analysis, and tooling integration.
- Experience with distributed tracing, SLO/SLI monitoring, and chaos engineering in production environments.
- Experience configuring system context, integrating MCP servers, using function calling, and creating structured domain prompts.
- Experience designing property-based tests, static analysis rules, and code-review workflows for AI-generated code.
- Ability to lead architecture decisions, mentor engineers, communicate tradeoffs, and establish team-wide AI coding standards.
- Preferred experience in financial risk management, high-frequency trading, clearing systems, internal developer tools, CLI extensions, custom LLM evaluation harnesses, local model deployments, or enterprise fine-tuning workflows.
Benefits
- Hybrid work arrangement requiring two days per week onsite in the Chicago office.
- Competitive total rewards package with annual target bonus opportunity and broad-based equity program.
- Health coverage, retirement benefits including a 401(k) and pension plan, education reimbursement, paid time off, and mental health benefits.
Tech Stack
About CME Group
CME Group operates global derivatives exchanges and a central counterparty clearinghouse, offering futures and options across interest rates, equities, FX, energy, agriculture, and metals via CME Globex and CME Clearing. It serves banks, asset managers, corporations, and professional traders with trading, market data, and risk management tools, earning fees from transactions, clearing, and data services. A public company headquartered in Chicago, it owns the CME, CBOT, NYMEX, and COMEX marketplaces.