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# Performance Engineer

- **Company:** Kforce Inc.
- **Location:** Shelton, CT, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), JavaScript (Programming Language), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Databases, Continuous Integration, DevOps, HP Loadrunner, Apache JMeter, Python (Programming Language), Systems Development Life Cycle, Reliability Engineering, Software Tools, Scripting, Cloud Platform System, Performance Testing, Cloud Monitoring, Neoload, Performance Monitor, Dynatrace
- **Published:** August 7, 2026
- **Apply:** https://www.dice.com/job-detail/7d59dc7b-0130-4de3-9810-f4b33376b074

## About the Role

* 5-7+ years in performance engineering/non-functional testing at enterprise scale
 * Experience with chaos engineering
 * Experience integrating performance validation into CI/CD and partnering with SRE/DevOps practices
 * Hands-on experience with AI-assisted engineering tools, including reviewing and validating AI-generated output, required
 * Hands-on expertise with performance tools (e.g., JMeter, k6, LoadRunner, NeoLoad, OctoPerf) and observability platforms (e.g., Dynatrace, cloud monitoring)
 * Proficiency scripting/automating in Java, JavaScript, or Python; Comfortable in cloud environments (AWS/Azure)
 * Strong communication and stakeholder leadership skills; Ability to translate technical findings into business impact

## Description

Kforce has a client that is seeking a Performance Engineer for a contract opportunity to work on-site in Shelton, CT 4 days a week. The candidate must also be able to interview in person in Shelton, CT., The Performance Engineer owns and leads the enterprise-wide Performance Engineering function, operating as a horizontal shared service supporting all product, platform, and engineering teams across the company., * Own the enterprise Performance Engineering charter as a horizontal shared service; Define engagement models, intake/prioritization, and performance-readiness standards across the SDLC

 * Design, script, execute, and report performance tests (load, stress, endurance, scalability) across high-volume ordering, kiosk, POS, loyalty, and payment flows; Establish baselines, workload models, and SLO/SLI-aligned KPIs
 * Identify and resolve bottlenecks across application, database, messaging, and infrastructure layers using observability signals (e.g., Dynatrace)
 * Embed automated performance validation into CI/CD pipelines (e.g., Azure DevOps) with baseline and threshold gating, and standardize reporting to reduce manual effort and variability
 * Partner with SRE/DevOps to define reliability-aligned targets and run controlled chaos-engineering experiments (fault/latency injection, dependency degradation) to validate resilience and recovery; Feed learnings into hardened runbooks, alerts, and automation
 * Define performance-readiness criteria and provide evidence-based go/no-go recommendations for releases; Own escalation paths for performance risk and support production performance-incident resolution; Produce executive-level reporting
 * Integrate AI-assisted workflows into performance planning, test-design acceleration, and results triage with human review; Maintain AI-consumable artifacts (NFRs, workload models, baselines, thresholds) and define guardrails for safe, policy-compliant AI use


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