Software Engineer, Backend
Walters, Nelson and Smith
Software Engineer, Backend
Walters, Nelson and Smith San Francisco, California, United States
About this position
Walters, Nelson & Smith | Precision in Engineering
Walters, Nelson & Smith (WNS) is a premier boutique engineering consulting firm dedicated to delivering high-impact solutions for complex structural and mechanical challenges. Founded on the principles of technical excellence and agile problem-solving, we bridge the gap between visionary design and practical execution.
Unlike larger, more rigid firms, WNS prides itself on a bespoke approach . We offer senior-level expertise and direct partner involvement on every project, ensuring that our clients receive sophisticated engineering insights tailored to their specific operational needs.
Core Specializations
- Structural Forensic Analysis: Identifying and resolving integrity issues in existing infrastructure.
- Sustainable Systems Design: Integrating energy-efficient mechanical solutions into modern builds.
- Precision Prototyping: Streamlining the transition from conceptual CAD models to functional, manufacture-ready designs.
- Regulatory Compliance & Risk Mitigation: Navigating the complex landscape of international engineering standards.
\"At Walters, Nelson & Smith, we don't just solve problems—we engineer resilience. Our focus is on building lasting partnerships through transparency, technical rigor, and a relentless commitment to quality\"
About The Role
As a Software Engineer, Backend, you will play a key role in designing, building, and maintaining scalable backend services that power our AI-driven products. You’ll collaborate closely with cross-functional partners in the Backend and AI teams to architect reliable APIs, optimize system performance, and ensure robust data flows that support our customer-facing and internal applications. This salaried, full-time position is ideal for an engineer with around 4 years of experience who is comfortable owning services end-to-end—from design and implementation through deployment, monitoring, and continuous improvement.
What You'll Do
- Design, implement, and maintain backend services, APIs, and data pipelines to support AI-powered applications and internal tools.
- Collaborate with product managers, frontend engineers, and AI/ML engineers to translate business and model requirements into scalable backend solutions.
- Write clean, testable, and maintainable code, including unit, integration, and end-to-end tests, following modern software engineering best practices.
- Architect and optimize database schemas, queries, and storage strategies for performance, reliability, and scalability.
- Integrate AI/ML models and services into backend systems, ensuring robust, low-latency, and secure inference and data processing paths.
- Participate in code reviews, technical design discussions, and architectural decisions within the Backend team.
- Monitor, troubleshoot, and improve the performance, reliability and observability of backend services in production.
- Contribute to continuous delivery and deployment pipelines, automating build, test, and release processes where possible.
- Document systems, services, and processes to ensure long-term maintainability and effective knowledge sharing across the team.
- Stay current with backend and AI-related technologies and propose improvements to our stack, tools, and development practices.
Qualifications
- Approximately 4+ years of professional software engineering experience with a primary focus on backend development.
- Strong proficiency in at least one modern backend programming language (e.g., Python, Java, Go, Node.js, or similar).
- Hands-on experience designing and building RESTful and/or gRPC APIs and backend services in a production environment.
- Solid understanding of software engineering fundamentals, including algorithms, data structures, design patterns, and distributed systems concepts.
- Experience with relational and/or NoSQL databases, including schema design, query optimization, and data modeling.
- Familiarity with integrating AI/ML services or working within AI-infused applications (e.g., model-serving, feature APIs, or data pipelines).
- Comfort working with cloud platforms (e.g., AWS, GCP, or Azure) and containerization/orchestration tools (e.g., Docker, Kubernetes).
- Experience with modern development practices, including code reviews, version control (Git), CI/CD, and automated testing.
- Strong debugging and problem-solving skills, with a focus on performance, reliability, and scalability.
- Effective communication skills in English and the ability to work collaboratively in a cross-functional, team-oriented environment.
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