Software Engineer Jobs in Sunnyvale, CA

Leads the design and delivery of scalable platform capabilities for Walmart’s restaurant delivery platform. Responsibilities include software development lifecycle ownership, cloud-native architecture, infrastructure and tooling, AI/ML integration, system design reviews, coding, testing, deployment, monitoring, mentoring engineers, stakeholder collaboration, and continuous improvement.

Leads scalable platform development across the full software lifecycle, including design, coding, testing, deployment, monitoring, and maintenance. Builds cloud-native systems, integrates AI/ML for automation, leads design reviews, mentors engineers, influences architecture, and collaborates with stakeholders to translate business needs into technical requirements. The role also drives engineering standardization, code quality, sustainability, and data-driven process improvement for restaurant delivery platforms.

Leads delivery of scoped software features and AI/ML model components across the full software development lifecycle. Responsibilities include coding, solution design, code reviews, debugging, CI/CD, automated testing, performance monitoring, defect resolution, and integrating generative AI capabilities. The role collaborates with cross-functional stakeholders, develops scalable and secure cloud-native systems, mentors peers, and drives continuous engineering improvement for a restaurant delivery platform.

Lead the design, development, deployment, and maintenance of scalable cloud-native platform capabilities for Walmart Connect’s sponsored search ad server. Build infrastructure, tooling, AI/ML frameworks, and distributed systems; conduct design reviews; drive software lifecycle activities; mentor engineers; influence architecture and technical decisions; and collaborate across teams to translate complex business needs into reliable, data-driven solutions.

Design, develop, and deliver software components, APIs, microservices, and UIs; integrate AI/ML features; implement CI/CD, automated testing, IaC, and containerized cloud deployments; monitor production, troubleshoot issues, and mentor junior engineers.

Leads full-stack software development across design, coding, testing, deployment, and support. Builds scalable, secure services, APIs, and AI/ML components using technologies including Java, React, NextJS, and Kubernetes. Responsibilities include code reviews, debugging, CI/CD, automated testing, performance monitoring, DevOps, stakeholder collaboration, technical solution design, and mentoring. The role is full-time and onsite in Sunnyvale, California.

Build scalable backend platform capabilities, infrastructure, tooling, and ML frameworks for Walmart’s Membership Experience Engineering team. Lead the full software development lifecycle, apply cloud-native architecture, design APIs and resilient systems, integrate AI and machine learning components, conduct design reviews, and ensure deployment, observability, and maintenance. Mentor engineers, influence technical decisions, collaborate with stakeholders, and use data-driven practices to improve engineering productivity and product outcomes.

Develop, implement, integrate, and verify motion control systems for autonomous vehicle platforms. Responsibilities include creating safety-critical motion control algorithms, analyzing performance in offline and on-road environments, and validating robustness against disturbances, failure modes, and environmental conditions.

Design, develop, and maintain scalable backend infrastructure and data-processing pipelines for Aurora’s static and dynamic mapping systems. Build reliable services for storing and serving map data, improve testing and performance, and collaborate with internal and external customers on system designs and features. The role focuses on distributed systems, data versioning, cloud-native technologies, and high-throughput mapping infrastructure supporting autonomous vehicles.

Develops real-time sensor-data algorithms and owns the design, implementation, testing, deployment, and maintenance of online calibration software for autonomous vehicles. Collaborates with software, hardware, manufacturing, and operations teams to keep vehicle sensors accurately aligned for safety-critical autonomy functions.

Build and maintain scalable data pipelines, ETL/ELT processes, data lake and warehouse infrastructure, and data platform tools. Develop cloud-based infrastructure using AWS and Terraform, optimize processing for reliability and cost, and implement monitoring, logging, governance, quality, and security practices. Collaborate with data scientists, analysts, autonomy engineers, and product teams to deliver reliable data solutions.

Develop real-time behavior-planning algorithms for autonomous vehicles, selecting safe and comfortable trajectories. Integrate motion planning with machine learning, build production-grade Aurora Driver software, and create metrics and testing workflows for algorithm iteration. The role requires strong Python or C++ programming experience in low-latency or real-time environments and experience productionizing motion-planning algorithms. GPU and machine-learning toolkit expertise is preferred.

Leads the design, development, deployment, and maintenance of scalable platform capabilities, infrastructure, tooling, AI/ML frameworks, and iOS advertising solutions. Builds reusable iOS frameworks and SDKs, applies cloud-native architecture, conducts system design reviews, integrates machine learning, and drives performance and reliability. Mentors engineers, influences technical decisions, collaborates cross-functionally, and uses experimentation, analytics, and data-driven practices to improve developer productivity and consumer applications.

Design and implement foundational data systems for AI, focusing on efficiency and performance at scale. Collaborate on systems that optimize data handling and contribute to research advancements.

Lead technical strategy and architecture for Developer Experience: build scalable build/test/delivery systems, improve CI/CD throughput, design internal platforms/APIs/SDKs/CLIs, integrate LLM/agentic tooling safely, mentor senior engineers, and drive cross-team initiatives to increase engineering velocity, reliability, and maintainability at organizational scale.

Join a small Applied Training team building Kubernetes-native research cluster and sandbox infrastructure for large-scale ML training. Design and implement cluster experiences (CLI, job schemas, operators), own Python SDKs for RL rollouts, work directly with customers and infra teams, document OSS training frameworks, and ship production-grade ML infrastructure solving distribution, scheduling, and isolation at scale.

Lead technical strategy and architecture for CoreWeave's orchestration platform (SUNK). Own critical orchestration components, drive cross-org initiatives in scheduling, quota enforcement, and hyperscale scaling. Mentor senior engineers, establish reliability and observability best practices, and ensure workloads run reliably and efficiently for large GPU ML training and inference clusters.

Take end-to-end ownership of a Kubernetes-based, multi-region data platform: architect for high availability and low latency, scale infrastructure, optimize CI/CD, implement observability and IaC, enforce cloud-native security, lead incident response, and ensure production readiness and capacity planning.

Design, build, and operate high-throughput, fault-tolerant ledger and settlement systems of record. Develop durable ledgering APIs, settlement orchestration, and treasury automation. Ensure data contract integrity for downstream finance, run production systems to SLOs, debug multi-layer issues, lead and mentor engineers, and use AI tooling to reduce operational toil.

Design and implement data platforms, manage data infrastructure, develop streaming architectures, improve performance, and ensure data compliance.

Lead design and implementation of high-performance, scalable integrations that ingest identity data from cloud and SaaS providers. Drive architecture and best practices, mentor backend engineers, partner with product and customer teams, and apply AI/ML models to streamline connector development and data modeling for Veza's Access Graph platform.

Architect and build AI-native, large-scale distributed systems for ITSM/ITOM products. Lead technical strategy, prototype and validate architectures, drive evidence-based experiments, establish patterns and best practices, mentor senior engineers, and collaborate across teams to deliver reliable, observable, and cost-effective agentic automation and operational intelligence.

Build, scale, and operate Moveworks AI cloud infrastructure and developer platform. Design secure, resilient multi-region/cloud systems; create IaC-driven CI/CD pipelines; manage Kubernetes/Istio clusters; collaborate with platform, ML, data, frontend, and security teams to meet performance, observability, and cost objectives.

Build and own distributed runtime infrastructure for agentic AI: session orchestration, lease-based distributed session management, event-driven pipelines, structured concurrency, observability, caching and state layers to support low-latency, correct, long-running agent workflows at scale.

Design, develop, and operate scalable production agentic systems and UI components. Own features end-to-end, integrate frontier AI SDKs, implement RAG/retrieval patterns, build testing and observability, mentor engineers, and raise engineering quality for AI-powered enterprise products.