Senior Software Development Engineer (US Federal)

Workday•Reston, VA

1d•$148,200 - $264,000•Hybrid

About The Position

This role will support one or more direct or indirect contracts with the U.S. Federal Government which, due to federal government security requirements, mandates that all Workday personnel working on the contracts be United States citizens (naturalized or native). As a Sr. Performance Engineer (Sr. Software Development Engineer), you will play a pivotal role in optimizing Workday’s Kubernetes platform and cloud infrastructure in AWS GovCloud. You will lead deep-dive performance troubleshooting, drive capacity forecasting models, and manage cloud infrastructure cost optimization. By establishing robust performance telemetry and load testing strategies, you will ensure our systems remain fast, scalable, cost-efficient, and resilient in air-gapped environments. You have a growth mindset and thrive in a collaborative, outcome-driven environment where cross-team partnership is key. You will be part of a team promoting a diverse and inclusive culture where you and your teammates are energized, engaged, and excited to solve complex engineering challenges together every day.

Requirements

U.S. Citizenship: Required due to federal government contract requirements.
Ability to obtain and maintain a U.S. Government TS/SCI security clearance with CI Polygraph. An active TS/SCI w/ CI Poly is strongly preferred.
5+ years of hands-on experience building, scaling, and maintaining production cloud infrastructure, DevOps pipelines, or platform engineering systems.
Proven proficiency (3+ years) with infrastructure automation tools such as Terraform or Terragrunt.
Hands-on experience (3+ years) managing continuous delivery pipelines using tools like Argo CD, Jenkins, or GitLab CI.
Proficiency in (3+ years) modern scripting or programming languages, with a preference for Go or Python.
Demonstrated ability (3+ years) to independently lead technical initiatives, troubleshoot distributed systems, and mentor junior engineers.
Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field (or equivalent military / practical engineering experience in lieu of a degree).

Nice To Haves

Deep production experience managing containerized workloads in AWS (ideally AWS GovCloud) using Kubernetes and Docker.
Practical experience implementing or managing air-gapped deployment methodologies and isolated cloud architectures.
Background in building robust monitoring, logging, and alerting systems for distributed platforms (e.g., Prometheus, Grafana, Splunk, etc).
Familiarity with federal security frameworks (e.g., FedRAMP, NIST 800-53, Zero Trust architecture).
DoD 8570/8140 compliance at IAT Level II or higher (e.g., CompTIA Security+, CySA+, CASP+) along with a current Computing Environment credential.

Responsibilities

Apply deep expertise in distributed systems to diagnose, profile, and resolve complex performance bottlenecks, latency spikes, and resource constraints across Kubernetes workloads in AWS GovCloud.
Build predictive capacity models, analyze system usage trends, and execute stress and load testing to ensure platforms scale seamlessly under peak federal workloads.
Track cloud resource utilization, right-size infrastructure, and implement FinOps strategies using AWS and Kubernetes tools to optimize infrastructure spend without compromising performance or security.
Build, maintain, and optimize APM tools, distributed tracing, and capacity alerting frameworks to detect performance degradations before they impact end users.
Utilize Terraform, Terragrunt, Docker, AWS, and Argo CD to automate infrastructure provisioning, auto-scaling policies, and continuous delivery pipelines.
Conduct performance testing, tuning, and capacity planning tailored specifically to air-gapped deployment methodologies and isolated cloud environments.
Work closely with software developers, security leaders, and platform engineers to establish performance benchmarks, conduct design reviews, and foster performance-aware architecture across teams.
Author technical performance reports, share capacity forecasting insights, and mentor team members on performance profiling and troubleshooting techniques.