Senior Software Engineer

Fabletics•California, CA

1d•$135,000 - $150,000•Remote

About The Position

Fabletics is currently looking for a Senior Software Engineer (full stack). This role involves designing, developing, and maintaining scalable, high-performance web applications using modern frameworks like React and Node.js within a cloud-native AWS environment. The engineer will leverage AI-assisted tooling to enhance productivity and code quality, prototype new technologies including AI capabilities, and build features for customer service workflows. A key aspect of the role is contributing to the integration of AI-powered capabilities to provide measurable value. The position requires owning the end-to-end feature lifecycle, designing distributed system architectures with careful consideration of tradeoffs, and collaborating cross-functionally with various teams to deliver high-impact features. The role also involves partnering with product and design to shape user experiences, leading code reviews, troubleshooting complex technical issues, and implementing observability practices. Designing robust APIs and data models, driving continuous improvements in engineering standards, and mentoring junior engineers are also key responsibilities. The Senior Software Engineer will influence technical direction, support CI/CD pipelines, and contribute to automated testing and DevOps practices.

Requirements

5+ years of professional software development experience, with strong full-stack expertise in JavaScript/TypeScript, React, Node.js, and RESTful APIs.
Experience using AI-assisted development tools (e.g., Claude, GitHub Copilot, ChatGPT) to improve workflows, with an understanding of their strengths, limitations, and tradeoffs.
Experience building or integrating systems that include AI/ML components (e.g., LLMs), especially in areas like text processing, classification, or automation, with awareness of considerations such as latency, cost, reliability, and data privacy.
Proven experience designing and building scalable, distributed systems in cloud environments, particularly AWS (e.g., EC2, S3, Lambda, RDS, CloudFormation).
Hands-on experience with containerization and orchestration technologies such as Docker and Kubernetes.
Strong understanding of application security principles, including authentication and authorization (OAuth2, JWT), and secure coding practices.
Experience identifying and resolving performance bottlenecks in high-traffic systems.
Solid understanding of observability practices, including monitoring, logging, and alerting.
Experience designing API contracts and data models with a focus on scalability and maintainability.
Familiarity with modern CI/CD pipelines and deployment tooling.
Experience working in agile environments using tools like Jira and Confluence.
Demonstrated ability to lead projects or small teams, make sound architectural decisions, and manage technical risk.
Comfort working with systems that may exhibit non-deterministic behavior, and the ability to design guardrails, monitoring, and fallback strategies where needed.
Experience mentoring engineers and contributing to a strong team culture.
Excellent problem-solving and debugging skills, with a track record of resolving complex production issues.
Strong communication skills, with the ability to collaborate effectively with technical and non-technical stakeholders.
Foundational AI literacy, including experience using generative AI tools, and a proactive mindset to experiment with new technologies to drive productivity and innovation.

Nice To Haves

Experience building or supporting customer-facing or operational tools (e.g., customer support platforms, internal tools, workflow systems) is a plus.

Responsibilities

Design, develop, and maintain scalable, high-performance web applications using modern frameworks such as React and Node.js within a cloud-native AWS environment.
Leverage modern development tools, including AI-assisted tooling where appropriate, to improve productivity, code quality, and team efficiency.
Prototype and evaluate new technologies—including AI capabilities—through rapid experimentation, and help determine when they are ready for production use.
Build and enhance features that support customer service workflows, including tools for automation, agent assistance, and improved customer interactions.
Contribute to the integration of AI-powered capabilities—such as response suggestions, summarization, classification, or workflow automation—where they provide clear, measurable value.
Own the end-to-end lifecycle of features—from technical design and architecture through implementation, deployment, and post-launch support—with a strong emphasis on scalability, performance, security, and reliability.
Design and evolve distributed system architectures, making thoughtful tradeoffs between performance, cost, reliability, and developer experience.
Collaborate cross-functionally with product, design, data, architecture, QA, and DevOps to deliver high-impact features aligned with customer and business needs.
Partner with product and design to shape intuitive, efficient user experiences for customer service agents, including those augmented by automation or intelligent assistance.
Lead and participate in code reviews, ensuring high-quality, maintainable code and adherence to engineering best practices.
Troubleshoot and resolve complex technical issues across environments, including issues related to system behavior, integrations, or AI-assisted features.
Implement and improve observability practices, including logging, monitoring, tracing, and alerting, and contribute to approaches for validating system behavior—including AI-assisted or non-deterministic components where applicable.
Design and maintain robust APIs and data models, ensuring scalability, consistency, and backward compatibility.
Drive continuous improvements in engineering standards, tooling, and development processes.
Mentor junior engineers and contribute to a collaborative, high-performing team culture.
Influence technical direction and contribute to architectural decisions and best practices across teams.
Support and enhance CI/CD pipelines, automated testing strategies, and DevOps practices to enable reliable, efficient releases.