Platform Engineer I

The Data Platform team builds and maintains the organization's enterprise knowledge catalog, knowledge graph, and unified data pipelines. We provide reusable data pipeline tooling for the enterprise and manage the entire BigQuery and analytics ecosystem. We focus on data accessibility, semantic connectivity, and automation to improve how data is discovered, processed, and utilized across the company.

You will build AI data agents that interact with our enterprise knowledge catalog, knowledge graph, and extensive analytics infrastructure. This role is responsible for automating complex data workflows, contributing to intelligent data pipeline tooling, and building scalable integrations that bridge our AI capabilities with our core data platforms.

Principal Accountabilities

• Agent Development: Design, build, and deploy AI data agents to query and navigate the enterprise knowledge graph, data catalogs, and analytics systems.

• Skill Creation: Develop modular Agent Skills to execute data retrieval, transformation, and analytical tasks.
• Agent Evaluation: Design and implement Agent Evals to test the reliability, accuracy, and factual consistency of agent outputs.
• Data Pipeline & Analytics Integration: Build intelligent integrations and reusable tooling that interface with our unified data pipelines and BigQuery ecosystems.

• Knowledge Integration: Collaborate with data engineers to ingest, curate, and expand the enterprise knowledge catalog and knowledge graph.

• Tool Utilization: Leverage Coding Agent tools (Claude, Anti Gravity, and GitHub Copilot) to accelerate technical delivery and code generation.
  

Required Skills & Qualifications

• Academic Foundation: Bachelor’s Degree (preferably in Computer Science, Information Systems, or a related discipline) accompanied by 1+ years of relevant hands-on engineering experience.
• Programming Languages: Strong proficiency in Python and Java.

• AI Frameworks: Hands-on experience building AI agents using Google ADK and LangChain.

• Agent Tooling: Direct experience developing Agent Skills and building Agent Evals.
  AI Assistants: Experience utilizing Coding Agent tools (Claude, Anti Gravity, GitHub Copilot) in the software development lifecycle.
  Execution: Ability to work proactively in a team environment and meet delivery timelines.
  

Preferred Qualifications (A Plus)

• Data Systems: Experience working with knowledge graphs, enterprise data catalogs, semantic data models, and data pipelines.

• Primary Cloud & Analytics: Hands-on experience with Google Cloud Platform (GCP) and deep knowledge of BigQuery.
• GitOps & Orchestration: Experience with GitOps practices and deploying applications to Kubernetes.
• Foundational Models: Experience working with Gemini models, Anthropic models, or GPT models.

• Multi-Cloud: Experience with other major cloud providers (AWS or Azure).
  

What You’ll Bring

• Apply strong hands-on development expertise in Java and Python, alongside proficiency in languages such as SQL, Go, Scala and Ruby.
• Accelerate delivery workflows using AI-aided development tools (Copilot, Claude, Gemini CLI, Antigravity CLI) and effective prompt engineering.
• Utilize foundational AI engineering concepts including context engineering, Retrieval-Augmented Generation (RAG) architectures, and AI model evaluation (evals).
• Build and consume robust REST and GraphQL APIs for enterprise data marketplace ecosystems.
• Navigate cloud platform environments (AWS, Google Cloud Platform, or Microsoft Azure), with hands-on Google Cloud experience strongly preferred.
• Enforce cloud security principles, API security protocols, secure coding standards, and established cloud application security frameworks.
• Manage containerized applications using Kubernetes, Docker, and registries such as Google Artifact Registry or Docker Hub.
• Automate workflows and infrastructure using Argo Workflows, Argo CD, Terraform, and Kubernetes Config Connector (KCC).
• Operate standard software delivery toolchains including Git, Maven, Jenkins, and automated CI/CD pipelines.
• Process diverse data storage and serialization formats including JSON, YAML, Avro, Parquet, and ORC.
• Execute comprehensive system testing to optimize data pipeline performance and API endpoint efficiency.
• Deliver projects using Agile methodologies and DevSecOps continuous integration and delivery practices.
• Solve complex technical problems independently and collaboratively within cross-functional teams, ensuring timely project delivery.
• Communicate technical concepts clearly across written and verbal formats while building strong interpersonal working relationships.
• Hold relevant cloud or DevSecOps professional certifications (AWS, GCP, or equivalent), which serves as a strong advantage.

CME Group: Where Futures are Made

CME Group is the world’s leading derivatives marketplace. But who we are goes deeper than that. Here, you can impact markets worldwide. Transform industries. And build a career by shaping tomorrow. We invest in your success and you own it – all while working alongside a team of leading experts who inspire you in ways big and small. Problem solvers, difference makers, trailblazers. Those are our people. And we’re looking for more.

At CME Group, we embrace our employees' unique experiences and skills to ensure that everyone’s perspectives are acknowledged and valued. As an equal-opportunity employer, we consider all potential employees without regard to any protected characteristic.

Important Notice: Recruitment fraud is on the rise, with scammers using misleading promises of job offers and interviews to solicit money and personal information from job seekers. CME Group adheres to established procedures designed to maintain trust, confidence and security throughout our recruitment process. Learn morehere.