Senior Backend Engineer, Platform Enablement

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Backend Engineer, Platform Enablement based in United States.

This remote role focuses on making performance testing and analysis easier for engineering teams to adopt and manage independently. You will build reusable backend platforms, developer tooling, self-service workflows, and AI-assisted engineering capabilities that help teams identify performance risks earlier. The role supports a shift from hands-on consulting toward scalable, self-service performance enablement across development and continuous integration workflows. You will work closely with engineering teams to turn complex performance challenges into durable platforms, documentation, and repeatable practices. The position combines backend engineering, platform development, performance optimization, and developer experience. You will also help shape how AI is incorporated into software design, implementation, testing, debugging, documentation, and automation. The environment is highly collaborative and asynchronous, with broad influence across research and development teams.

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Accountabilities:

• Build and continuously evolve reusable backend platforms and developer tooling that support performance testing, analysis, benchmarking, and optimization.
• Create self-service workflows, documentation, templates, diagnostics, and AI-assisted engineering capabilities that reduce reliance on bespoke performance support.
• Enable feature teams to integrate performance testing into their own development and continuous integration workflows.
• Apply AI-enabled development practices to accelerate implementation, testing, debugging, documentation, and engineering automation.
• Improve performance results, reporting, trend visibility, and evidence-based decision-making so engineering teams can evaluate performance independently.
• Help establish the documentation, templates, standards, and guidance required to expand self-service adoption across research and development.
• Influence engineering teams to make performance testing and analysis an integral part of development and release preparation.
• Turn hands-on engagements and recurring performance challenges into generalized capabilities that can be adopted by multiple teams.
• Provide technical expertise for complex performance questions, tooling improvements, and new platform capabilities.
• Collaborate asynchronously and cross-functionally with development teams to build solutions that scale beyond individual engagements.

Requirements:

• Demonstrated experience building backend or platform software and developing internal platforms or developer-facing tooling.
• Experience partnering with software development teams to improve engineering workflows, productivity, and operational practices.
• Experience applying AI-assisted development practices across the software lifecycle, including implementation, testing, debugging, documentation, or automation.
• Practical experience with software performance, such as performance analysis, optimization, benchmarking, or leading performance-related engineering improvements.
• Hands-on experience with Kubernetes and k6, along with Amazon Web Services, Google Cloud Platform, or comparable cloud infrastructure.
• Ability to design durable, reusable solutions that support broad adoption through strong systems thinking.
• Strong backend engineering and platform design skills, with an understanding of scalable developer infrastructure and self-service capabilities.
• Clear written and verbal communication skills, with the ability to influence and collaborate effectively across teams without relying on direct authority.
• Ability to work effectively in an asynchronous environment and collaborate broadly across research and development organizations.
• Strong problem-solving skills and the ability to turn complex or ambiguous performance challenges into practical, scalable engineering solutions.

Benefits:

• Fully remote position within the United States.
• Base salary range of $156,800–$235,200 USD.
• Benefits supporting health, finances, and overall well-being.
• Flexible paid time off.
• Equity compensation and employee stock purchase plan.
• Growth and Development Fund to support professional learning and career development.
• Parental leave.
• Team member resource groups and an inclusive workplace environment.
• Support for accessible and inclusive interview experiences, including reasonable accommodations when needed.
• Opportunities to work on AI-assisted engineering practices, backend platforms, developer tooling, and large-scale performance enablement initiatives.

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How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

 Why Apply Through Jobgether? 

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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