Performance Engineer

Princeton IT Services, Inc; St. Louis (MO); Hybrid; USD 100,000 - 130,000; Full time

Job summary

Princeton IT Services, Inc is seeking a Performance Engineer based in Saint Louis, MO or willing to relocate. In this role, you will identify and resolve performance bottlenecks across distributed systems and cloud environments. Candidates should have strong experience with Spring Boot, cloud platforms, and performance debugging techniques.

Your responsibilities will include defining service-level objectives and leading performance incident analyses using advanced techniques. Join a dynamic team to enhance high-transaction platforms with your expertise.

Qualifications

• Extensive experience with performance bottlenecks in distributed systems.
• Familiarity with high-scale, multi-region platforms.
• Experience in analyzing application and cloud behavior.

Responsibilities

• Define service-level objectives and performance budgets.
• Lead root-cause analysis for performance incidents.
• Architect distributed tracing strategies.

Skills

Container orchestration

Spring Boot internals

Performance debugging

AWS

Distributed tracing

Tools

Dynatrace

Kubernetes

Docker

Job description

Job Title: Performance Engineer

Location: Saint Louis, MO (Locals) or 100% willing to relocate – will work 3 to 4 days onsite.

Job Type: Long term Contract

Overview

In this role, the lead will be responsible for identifying and resolving end-to-end performance bottlenecks across distributed systems, Spring Boot services, middleware components, and hybrid cloud environments (private cloud + AWS). This role goes far beyond traditional testing by deeply analyzing container orchestration, networking paths, and system interactions under load. This position maps full system workflows, sets realistic latency budgets, and ensures each component meets its SLOs. Ideal candidates have extensive experience with high-scale, multi-region, and high-transaction platforms (e.g., financial systems, payment processing, or large enterprise SaaS) running in a Cloud environment.

Key Responsibilities

• Define service-level objectives (SLOs), performance budgets, and latency/throughput targets across services.
• Architect and champion comprehensive distributed tracing strategies (Dynatrace, AWS X‑Ray, etc.).
• Analyze application, platform, and cloud behavior using deep‑dive techniques such as heap dumps, thread dumps, flame graphs, GC logs, network traces, and storage I/O profiling.
• Review service and system architectures for performance risks (e.g., synchronous hops, excessive dependencies, misconfigured connection pools, poor cache placement).
• Conduct and lead root‑cause analysis for performance incidents in production and pre‑production environments.
• Develop capacity models and performance baselines for services running across cloud environments.

Areas of Expertise

• Application Layer: Spring Boot internals, JVM tuning, thread/heap management, concurrency debugging, GC optimization
• Container Runtime: PCF, Docker, container resource limits, CPU throttling, memory pressure
• Orchestrators: PCF, Kubernetes, ECS (autoscaling, pod health, scheduling issues)
• Networking: Service-to-service hops, TLS overhead, DNS, routing, load balancer configs (F5, Nginx, ALB/NLB), service mesh performance
• Storage: Latency, IOPS constraints, distributed file system behavior
• Caching & Middleware: Redis, Hazelcast, NATS, Kafka, RabbitMQ configuration and throughput tuning
• Databases: Connection pool tuning, slow queries, indexing, replication lag
• Cloud Layer: AWS compute/storage/network performance, regional latency, cross-cloud traffic patterns