Software Engineer Jobs in Santa Clara, CA

Develop platform software for SOCs, including drivers, BSP, CI/CD automation, OS and multimedia driver bring-up, debugging, and system-level triage. Collaborate with OEMs and global engineering teams across the full product lifecycle from pre-silicon modeling through production. Contribute to architecture definition, boot, security, reliability, resiliency, and embedded-system software for Windows and Linux platforms.

Develop and maintain reliable, secure, and high-performance GPU cluster infrastructure for AI researchers. Design solutions for cluster validation, monitoring, operations, reliability, and performance at scale. Research and apply AIOps and Agentic AI to reduce operational toil, support self-service improvements, and participate in on-call operations. The role also involves software development on Linux, container orchestration, automated deployments, and potentially full-stack platform development and Slurm scheduling.

Design and deliver full stack, client-facing loyalty experiences and embeddable placements. Lead end-to-end system and browser-side architecture, ensure scalability, performance, privacy, and compatibility across partner surfaces. Integrate AI/ML personalization safely, own features through implementation and operations, collaborate with product/data/design/partner teams, and mentor engineers while defining patterns and best practices for embedded cross-team solutions.

Develop high-performance dataplane software for TeraWave satellite communications points of presence. Responsibilities include building C/C++ packet-processing applications, optimizing 100G/400G line-rate performance, implementing routing and tunneling protocols, integrating SmartNIC and FPGA accelerators, architecting distributed systems, conducting code reviews, mentoring engineers, and collaborating with hardware, platform, and networking teams.

Develops and validates autonomous driving software across perception, localization, planning, prediction, and control modules. Responsibilities include software implementation, ML data pipeline development, driving log analysis, simulation and emulation, vehicle testing, algorithm research, and collaboration with Isuzu teams, partners, and research institutions. The role requires Python and C++, machine learning frameworks, robotic middleware, embedded deployment, real-time validation, and familiarity with automotive systems, CAN, functional safety, and autonomous driving architectures.

Design, build, and operate secure, high-performance sandboxed runtime environments for multi-tenant Kubernetes workloads. Develop GPU-aware scheduling, isolation, and resource management strategies; integrate container runtimes, lightweight virtual machines, and virtualization technologies; optimize container, VM, I/O, and GPU performance; conduct profiling and benchmarking; and contribute to Linux, runtime, virtualization, GPU, and security architecture.

Design, develop, and maintain large-scale backend systems and APIs. Lead technical design and implementation of distributed, service-oriented and event-driven architectures. Perform code reviews, ensure security and performance, troubleshoot complex production incidents, and lead root-cause analysis and remediation. Hybrid role with 3 days in-office and ~20% domestic travel.

Design and develop platform driver code across kernel and user space to model, stress, and verify hardware. Collaborate with hardware, software, and mechanical engineering teams to create test suites, support prototype bring-up, and enable large-scale AI datacenter deployments. Contribute to platform software architecture, system validation, and a collaborative startup culture.

Design and implement high-performance datapath features for load balancing, firewall rules, and Layer 7 protocols. Build scalable networking and security systems using C or C++, data structures, algorithms, and Unix/Linux optimization. Own architectural projects from conception through large-scale deployment while applying advanced knowledge of DNS, HTTP, TCP/IP, and SSL/TLS. Use AI tools to improve engineering workflows and problem-solving.

Design and implement high-performance datapath features for load balancing, firewall rules, and Layer 7 protocols. Build scalable networking and security applications using C or C++, advanced data structures and algorithms, and Unix or Linux systems. Own complex architectural projects from concept through deployment while applying expertise in DNS, HTTP, TCP/IP, and SSL/TLS to enhance global network infrastructure.

Defines the technical vision, architecture, and roadmap for autonomous-driving simulation, validation, and reinforcement-learning infrastructure. Establishes scalable, deterministic, high-fidelity platform standards; leads complex cross-organizational initiatives; guides simulation abstractions, APIs, modeling, and execution systems; influences senior leaders and investment decisions; improves engineering quality and velocity; and mentors senior technical staff. Preferred experience includes autonomous-vehicle or robotics simulation, game or physics engines, and reinforcement-learning infrastructure.

Lead architecture and technical direction for large-scale workflow and automation platforms. Build prototypes, validate architectural ideas through experiments, improve AI-native and agentic execution, and address performance, reliability, data, UX, safety, and cost challenges. Influence architecture across teams, establish reusable engineering patterns, participate in design reviews, mentor senior engineers, and guide platform modernization for high-volume enterprise systems.

Own the architecture and technical strategy for Square’s go-to-market systems. Build and operate production AI agents, automated workflows, and integrations that improve sales productivity. Lead complex initiatives through architecture, implementation, testing, deployment, and operations while establishing AI evaluation, observability, security, reliability, and human-oversight practices. Partner with Sales, Product, Data, and Engineering leaders to translate business needs into scalable solutions, make build-versus-buy decisions, mentor engineers, and improve business impact through data and user feedback.

Architect, develop, and maintain scalable system test automation infrastructure for ZIA Core Datapath. Build automation suites validating cloud firewall, tunneling, load balancing, IPS/IDS, routing, and switching technologies. Perform functional, integration, performance, and scale testing; troubleshoot complex network, HTTP/SSL, and firewall issues; optimize regression cycles; and mentor engineers.

Architect, develop, and maintain scalable system test automation infrastructure for ZIA Core Datapath, a cloud security platform processing over 400 billion daily transactions. Build automation suites for L4-L7 technologies, validate firewall and tunneling stacks, perform functional, integration, performance, and scale testing, troubleshoot complex network and customer issues, optimize regression cycles, and mentor junior engineers.

Architect and build evaluation metrics, statistical and ML analyses, dashboards, and pipelines for autonomous driving systems. Analyze simulation and on-road time-series data, evaluate perception, prediction, and planning models, identify anomalous behavior, and support release-gating and safety decisions. The role requires production Python development, C++ codebase work, cross-team technical leadership, and integration of advanced AI models for scenario classification and validation prioritization.

Lead the architecture and strategy of autonomous vehicle evaluation systems. Develop metrics, statistical and machine-learning methods, automated workflows, dashboards, and release-gating criteria to assess AV performance, identify regressions, and support safety decisions. Collaborate with autonomy, simulation, systems, safety, and data teams across the development lifecycle. Analyze large-scale time-series data, investigate anomalies, influence technical strategy, and provide system-level insights for validated autonomous driving deployment.

Develop scalable backend services, APIs, event-driven workflows, metadata pipelines, configuration tools, deployment controls, and observability for vehicle data collection across fleets. The role owns production systems, improves data quality and campaign monitoring, leads cross-team technical initiatives, and contributes through architecture reviews, testing, code reviews, mentorship, and production support. Collaboration spans AI research, data engineering, vehicle engineering, autonomy, privacy, product, and operations teams.

Own the architecture and technical strategy for Square’s go-to-market technology stack. Build and operate production AI agents, automated workflows, and integrations that improve sales productivity. Lead complex technical initiatives, establish AI reliability and security guardrails, define evaluation metrics, and guide build-versus-buy decisions. Partner with Sales, Product, Data, and Engineering leaders while mentoring engineers and remaining hands-on across design, implementation, testing, deployment, and operations.

Build and ship end-to-end features for AiPrise’s compliance orchestration and AI agent platform. Develop REST APIs, microservices, data pipelines, case management workflows, vendor integrations, and customer-facing tools. Write tested, documented code; participate in reviews; debug production issues; improve performance, reliability, and observability; and collaborate with product, compliance, and customer success teams.

Integrate software across embedded systems, hardware interfaces, controls, and user-facing applications for advanced energy medical devices. Develop integration plans, test cases, procedures, and reports; perform software verification and validation; review code; troubleshoot prototypes; investigate root causes; and support system bring-up and stabilization. Collaborate cross-functionally to ensure safety, reliability, and performance requirements are met.

Build a Physical AI security platform covering threat modeling, cyber risk analysis, intrusion detection, security testing, investigations, and agentic workflows. Develop full-stack features with TypeScript, React, and a typed backend language; integrate web applications, AI agents, and autonomous devices; deploy LLM-powered capabilities; and model relational domains with traceability and durable asynchronous workflows.

Design and develop scalable, high-performance data and API infrastructure for real-time processing. Mentor engineers and collaborate with teams to enhance AI model evaluations.

The role involves designing and building data pipelines for analyzing user feedback on AI models, ensuring data quality and infrastructure scalability.

Leads software engineering projects and developer teams building distributed microservices and cloud-based backend solutions. Collaborates with product managers, mentors engineers, evaluates code, and addresses regulatory and customer needs. Uses technologies including Java, Python, Go, Node.js, SQL, AWS, Docker, Kubernetes, relational databases, and NoSQL databases while staying current with emerging technologies and AI tooling.