Description

SMTS Performance Engineer, GCP

As a Performance Engineer in the Hyperforce GCP organization working with the Agentforce Service team, you will be at the cutting edge of AI adoption in contact centers. Our main focus moving forward is the AI-informed transformation of enterprise service, providing significant opportunities to work on cutting-edge generative AI, including autonomous agents that can reason and act.

A critical priority for this role is our multi-substrate expansion. We are currently adding support for the GCP substrate for SCRT2 channels, which will offer customers greater choice and flexibility. You will be instrumental in these efforts and will be responsible for:

• Characterizing the performance of Agentforce Service specifically on a GCP substrate.

• Developing sophisticated tests for complex load simulations and comprehensive end-to-end automation across multiple hardware and software tiers.

• Utilizing AI-powered analysis (such as LLM-driven JFR pipelines) to significantly reduce performance analysis time.

• Collaborating with cross-functional teams to provide product and automation expertise for patches, research projects, and capacity planning.

Required Skills:

• Familiarity with the architecture and fundamentals of GCP infrastructure and a working knowledge of GCP architecture.

• Strong knowledge of Java and SQL.

• Distinguished track record in performance engineering for technically demanding projects.

• Experience with performance testing, analysis, troubleshooting, and optimizing enterprise software at scale.

• BS, MS, or PhD in Computer Science or equivalent work experience.

• Understanding of throughput, latency, memory/CPU utilization, JVM, and JIT.

• Knowledge of HTTP load generation software (e.g., JMeter, LoadRunner) and web technologies (AJAX, REST, JSON).

Desired Skills:

• 5+ years of experience working on multiple releases with short cycles (3-6 months).

• Experience with generative AI technologies, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).

• Familiarity with autonomous agent orchestration and AI-driven workflows.

• Exposure to web/mobile performance testing and UI analysis.

• Knowledge of message queues (e.g., Apache Qpid, RabbitMQ) and clustering technologies.

• Familiarity with application servers (e.g., Jetty, Weblogic, JBoss).