Principal Performance and Scale Engineer

The Performance and Scale Engineering team is looking for a Principal Performance Engineer to join the PSAP (Performance and Scale for AI Platforms) to lead the
AI Engineering Tools Performance and Scale efforts within the PSAP team.

AI Engineering Tools organization is building an open‑source, end‑to‑end platform for building generative‑AI solutions on RHEL and OpenShift. From high‑volume Data Processing pipelines and Retrieval‑Augmented Generation (RAG) services to Agentic / MCP orchestration and a production‑ready Llama Stack, each scrum team ships a critical layer of our stack. As Principal Performance & Scalability Engineer, youll be the technical leader who ensures every layer performsand scalesflawlessly in the hands of developers and enterprise customers.

This role needs a seasoned engineer that thinks creatively, adapts to rapid change, and has the willingness to learn and apply new technologies. You will be joining a vibrant open source culture, and helping promote performance and innovation in this engineering team. The border mission of the Performance and Scale team is to establish performance and scale leadership of the product and cloud services portfolio. The scope includes component level, system and solution analysis and targeted enhancements. The team collaborates with engineering, product management, product marketing and customer support as well as hardware and software ecosystem partners.

our commitment to open source innovation extends beyond our products - its embedded in how we work and grow. embrace change especially in our fast-moving technological landscape and have a strong growth mindset. That's why we encourage our teams to proactively, thoughtfully, and ethically use AI to simplify their workflows, cut complexity, and boost efficiency. This empowers our associates to focus on higher-impact work, creating smart, more innovative solutions that solve our customers' most pressing challenges.

What you will do:
Define measurable KPIs / SLOs for throughput, latency, footprint, and cost across all AI Engineering Tools components.
Own and iterate on the performance roadmapfrom micro‑benchmarks to multi‑cluster scale tests.
Champion a performance‑first engineering culture
Formulate performance test plans and execute performance benchmarks to characterize performance, drive improvements, and detect performance issues through data analysis and visualization
Develop and maintain tools, scripts, and automated solutions that streamline performance benchmarking tasks.
Work closely with cross-functional engineering teams to identify and address performance issues. For eg.
RAG: profile vector DBs (PGVector, Milvus) and embedding models, tune ANN indexes and cache paths.
Agentic/MCP: stress‑test agent orchestration graphs, reduce tail latency of multi‑step chains.
Llama Stack: Performance and Capacity Measurement
Partner with DevOps to bake performance gates into GitHub Actions/OpenShift Pipelines.
Explore and experiment with emerging AI technologies relevant to software development, proactively identifying opportunities to incorporate new AI capabilities into existing workflows and tooling.
Triage field and customer escalations related to performance; distill findings into upstream issues and product backlog items.
Publish results, recommendations, and best practices through internal reports, presentations, external blogs, and official documentation.
Represent the team at internal and external conferences, presenting key findings and strategies.