Software Engineer Jobs in San Jose, CA

Conduct AI research for semiconductor manufacturing equipment, develop and evaluate solutions, translate research ideas into Python or C/C++ code, contribute to existing and new codebases, and share technical insights with the AI research team. Interns will complete meaningful project work, apply Lean principles, collaborate across cultures, and support the organization’s AI/ML research roadmap.

Design, build, and operate services powering card issuance, transaction authorization, wallet provisioning, 3-D Secure, and disputes. Own features end-to-end within a microservice, event-driven architecture, write well-tested code, participate in reviews, and perform operational ownership including on-call and incident response. Leverage AI developer tools to improve velocity and quality.

Build the enterprise platform for an AI creative product, including workspaces, permissions, SSO, audit logs, usage-based billing, invoicing, payment integrations, and security foundations. Develop backend services, APIs, and polished React/Next.js administrative interfaces for multi-tenant customers. Collaborate with founders, sales, and customers to define and ship enterprise features while taking increasing ownership of platform surfaces.

Lead design and delivery of secure storage software across OS, kernel drivers, microservices and containerized environments. Act as security consultant, manage vulnerability backlog and remediation, influence architecture and compliance (FIPS, Common Criteria, DISA STIG), mentor engineers, and evaluate vendors and technologies to ensure product security and certification readiness.

Design, build, test, ship, and operate services powering card issuance, transaction processing, and disputes. Own features end-to-end within a microservice and event-driven architecture, write well-tested code, participate in on-call incident response, and leverage AI tools to improve development velocity and quality while collaborating with cross-functional teams.

Lead DevOps engineering initiatives and developer teams building cloud-based solutions for regulatory and customer needs. Design and deliver systems using cloud-native technologies, microservices, machine learning platforms, containers, infrastructure-as-code, deployment tools, and distributed databases. Mentor engineers, evaluate emerging technologies, collaborate with product managers, and promote iterative Agile delivery practices.

Develop optimized GPU algorithms and high-performance machine learning solutions for vector search, databases, and data processing. Responsibilities include designing, implementing, benchmarking, debugging, and optimizing C++, CUDA, and Python libraries; developing clustering and visualization algorithms; collaborating cross-functionally; and contributing to open-source projects such as cuML, cuVS, and RAFT.

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.

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.

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.

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.

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.

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.

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.

Lead design and delivery of production-grade data pipelines, models, and data products for Go-To-Market and revenue analytics. Build scalable ETL/streaming architectures, semantic layers, and schema governance; embed LLM-assisted workflows and AI coding tools; apply software engineering best practices for CI/CD, testing, observability, and mentoring.

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.

Build and operate Block’s data platform, including warehousing, orchestration, business intelligence, governance, and agentic workflows. Develop reliable Python services, developer tools, and Terraform infrastructure for petabyte-scale data. Partner with data practitioners and product teams, establish engineering standards, provide technical direction, and mentor engineers while ensuring security, reliability, observability, usability, and data governance.