Staff Agentic Software Engineer

About the role

CME Group is seeking a senior Staff Agentic Software Engineer to join a dynamic team responsible for mission-critical Real-time Positions & Risk Management Systems. This role drives the technical evolution of financial platforms and transforms engineering workflows by leading the transition from traditional software development to an agentic engineering paradigm. You will leverage advanced LLM coding tools (e.g., Gemini CLI, Antigravity) to build high-performance systems faster, safer, and at greater scale while balancing AI-driven velocity with strict safety, low-latency, and zero-downtime requirements for CME Group’s core clearing and risk management functions.

Responsibilities

• Lead the architecture, design, and development of high-volume, low-latency Java applications on Google Cloud Platform (GCP) for mission-critical systems, ensuring ultra-high availability, low jitter, and thread safety.
• Drive the team’s shift toward agentic software engineering by standardizing toolchains, system prompts, context repositories, and agentic loops across the development lifecycle.
• Build and maintain shared agent infrastructure, including repo-level agent context, MCP server integration, codebase indexing pipelines, and local developer tooling that feed deep, domain-specific context into LLM agents.
• Design dynamic evaluation harnesses, automated test suites, and CI/CD guardrails tailored to audit, test, and validate AI-generated code for concurrency bugs, memory leaks, and performance regressions.
• Maintain and enhance high-throughput CI/CD automation pipelines for seamless, secure, and reliable software delivery into production.
• Mentor engineers through the workflow shift, leading hands-on workshops to train traditional software developers into proficient AI-native engineers.
• Drive architecture decisions across team boundaries, articulating tradeoffs clearly to engineers and stakeholders.
• Operate under pressure and on-call for systems where failure has direct financial or regulatory impact.
• Elevate team capabilities through rigorous code reviews, design reviews, pairing, and active mentorship.
• Contribute to development tooling and engineering culture initiatives, championing an AI-first engineering culture.

Requirements

• Bachelor’s degree or higher in Computer Science, Mathematics, Financial Engineering, or a related field, with 8+ years of hands-on experience building, deploying, and maintaining scalable real-time systems across the full stack.
• Expert-level proficiency in Java and the Spring framework, with deep experience designing and debugging multi-threaded concurrent applications, lock-free data structures, memory management, thread pools, and race condition diagnostics.
• Hands-on experience with AI coding agents (e.g., Gemini CLI, Claude Code, Codex) in real production workflows, including multi-step agent tasks, agent-authored PRs, and agent-driven test generation.
• Deep experience with Google Cloud Platform (GCP) services (GKE, Pub/Sub, BigQuery, Cloud Run, Dataflow) and real-time messaging frameworks (Kafka, MQ, Flink).
• Strong proficiency in SQL, Postgres DB, and Python (for scripting, automated evals, data analysis, or tooling integration).
• Experience with distributed tracing, SLO/SLI monitoring, and chaos engineering in production environments where system failure carries direct financial or regulatory impact.

Agentic Engineering Skills

• Daily operational fluency with CLI and terminal-based agent environments (Claude Code, Gemini CLI, Codex) and agentic IDEs (Cursor, Antigravity).
• Direct experience configuring system context, building or integrating Model Context Protocol (MCP) servers, function calling, and structured domain-prompting.
• Proven track record designing property-based tests, static analysis rules, and code-review workflows to catch AI hallucinations, edge-case failures, and security vulnerabilities.
• Demonstrated ability to establish team-wide AI coding norms, measure developer outcome velocity, and champion an AI-first engineering culture.

Qualifications

• Experience developing software for financial risk management, high-frequency trading, or clearing systems.
• Experience building internal developer tools, CLI extensions, or custom LLM evaluation harnesses.
• Familiarity with local model deployments or fine-tuning workflows for enterprise dev environments.

Pay

The pay range for this role is $125,800–$209,600. Actual salary offered will depend on factors including relevant experience, skills, education, and internal equity.

Benefits

• Annual target bonus opportunity.
• Broad-based equity program, allowing employees to become company owners.
• Comprehensive health coverage.
• Retirement package including both a 401(k) and an active pension plan.
• Highly competitive education reimbursement provisions.
• Paid time off and mental health benefits.