IBM Data Platform is building the leading hybrid AI and Data product for enterprises. We are delivering cutting-edge agentic and data capabilities so that clients can change the way they work. We are on the verge of a paradigm shift in enterprise productivity—and IBM Data Platform is defining what that future will look like. Are you ready to contribute to this new era of technology and help solve some of the world's most challenging problems? If so let’s talk.
IBM is seeking skilled and detail-oriented engineers to join our Benchmarking team.
In this role you will build and deploy cutting edge agent and data software solutions to evaluate features capabilities and performance. You will run benchmarks and assessments to inform strategic product positioning. You are both a gifted engineer and product strategist.
Key Responsibilities:
- Deploy and configure IBM and competitor software stacks on hyperscaler infrastructure (AWS Azure GCP).
- Execute benchmarking test plans using industry-standard tools and frameworks.
- Collect analyze and visualize performance data using tools like Grafana Prometheus and custom dashboards.
- Contribute to the development and refinement of benchmarking scripts and automation (e.g. using JMeter Locust or custom Python).
- Collaborate with product managers performance engineers and architects to interpret results and identify optimization opportunities.
- Maintain rigorous documentation of test environments configurations and outcomes.
- Stay current on emerging benchmarks and performance testing methodologies relevant to data platforms and agentic systems.
- Master’s degree in Computer Science Engineering or related field.
- Familiarity with performance testing tools (e.g. JMeter Locust LoadRunner).
- Experience deploying and tuning software on cloud infrastructure (e.g. AWS EC2 GCP Compute Engine).
- Basic proficiency in scripting languages (e.g. Python Bash) and infrastructure-as-code tools (e.g. Terraform Ansible).
- Ability to interpret performance metrics and communicate findings clearly.
- Strong attention to detail and organizational skills.
- PhD in Business Computer Science Engineering or related field.
- Experience with distributed systems databases and container orchestration (e.g. Kubernetes).
- Familiarity with competitive data platforms or agentic frameworks.
- Exposure to IBM’s data and AI products