Software Engineer Jobs in Oakland, CA

Build and operate ingestion and reconciliation pipelines that match card-network and partner reports against internal transactions. Develop reporting products, produce standardized journals for accounting, support tax and regulatory filing systems, handle sensitive PII for compliance, debug production issues, and collaborate with finance, product, and data teams to automate and scale reconciliation and reporting.

Design, build, test, and maintain enterprise integrations and automations across procurement, finance, and supply chain systems using MuleSoft and Zip iPaaS. Develop Python tools, write and optimize SQL, collaborate with stakeholders, ensure scalability and security, monitor production integrations, and contribute to documentation and DevOps practices.

Build and ship small end-to-end features across frontend and backend systems for research infrastructure. The role involves learning from experienced engineers, using AI coding tools, pair programming, collaborating with the team, and deploying production software. Candidates should have 0–3 years of experience, a strong computer science or related educational background, experience using AI coding assistants, and demonstrated work through GitHub repositories or side projects.

Own full-stack product features from technical scoping through deployment and post-launch iteration. Design schemas, APIs, and business logic; build user-facing applications across frontend, backend, and databases; collaborate with ML researchers, product, design, and engineering; incorporate user feedback; and improve development, testing, and deployment practices.

Build and operate highly reliable card-issuing software and tooling across authorization, clearing, settlement, certification, and network integrations. Serve as a technical expert on card-network specifications, protocols, mandates, and production behavior. Lead complex cross-team engineering work, debug protocol-level issues, influence network requirements, mentor engineers, improve platform reliability, and participate in on-call support for critical financial systems.

Staff Software Engineer responsible for building and operating Block’s card issuing platform at the network boundary. The role requires deep expertise in card networks, ISO 8583, authorization and clearing flows, certifications, mandates, and direct network connectivity. Responsibilities include writing production code, developing conformance tooling, debugging protocols, leading cross-team technical initiatives, influencing network requirements, mentoring engineers, supporting AI-assisted development, and participating in on-call operations for critical financial systems.

Develop and ship autonomy software for outdoor, production robots across perception, localization, state estimation, motion planning, and controls. Build fleet coordination, simulation and CI, logging/telemetry pipelines, and operator tools. Validate on real hardware, support field deployments, and ensure software degrades gracefully at remote sites.

Design, build, deploy, and maintain critical software supporting scientific experiments, instruments, data systems, and infrastructure. Translate ambiguous research needs into reliable software milestones, develop integrations and high-volume data workflows, solve concurrency and performance issues, and improve testing, observability, and release practices. The role also includes architecture decisions, code review, mentoring, technical leadership, and collaboration with scientists and engineers.

Build end-to-end full-stack features for cloud and factory-floor edge applications. Implement offline-capable, low-latency UIs and backend services, design APIs, write tests, troubleshoot production issues, and collaborate on shared libraries and developer tooling to support factory operators and supervisors.

Build and operate critical software for power-campus design, construction, simulation, optimization, equipment integration, and energy management. Own technical areas, shape roadmaps, make architectural decisions, debug production systems, establish data models and interfaces, improve testing and observability, and mentor engineers. The role collaborates across power systems, construction, robotics, and company leadership to deliver reliable software interacting with physical infrastructure.

Own the Linux user-mode runtime, driver, and HAL interfaces for a Fabric accelerator. Responsibilities include runtime library design, compiler and kernel-driver integration, memory and resource management, ML framework backends, pre-silicon bring-up using simulation, emulation, QEMU, and FPGAs, and comprehensive runtime testing. Collaborate across compiler, architecture, verification, and kernel teams to support first-silicon deployment.

Own development of a Linux kernel-mode driver for a custom Fabric accelerator, including memory management, SMMU/IOMMU integration, MMIO, interrupts, power management, firmware, and user-space interfaces. Lead pre-silicon enablement using QEMU, simulation, emulation, and FPGA platforms; manage Linux boot and first-silicon bring-up. Debug complex hardware and kernel issues, establish automated testing, and collaborate with architecture, verification, compiler, and hardware teams.

Build and maintain AI-driven workflows, agentic systems, automated operations tooling, cloud infrastructure, and CI/CD pipelines. Handle monitoring, incident triage, backend production issues, and field-operations support. Contribute across the full stack, communicate technical decisions to non-engineering stakeholders, and improve manual processes through automation. Required capabilities include cloud infrastructure, LLM and MCP development, Linux, CI/CD, full-stack engineering, and strong communication.

Build and operate ingestion, reconciliation, and reporting systems that reconcile card-network and partner settlement files against internal transactions. Deliver end-to-end features for traceability, accounting journals, tax and regulatory reporting, and compliance tooling while ensuring reliability, scalability, and data privacy.

Own and improve data-intensive Python backend and full-stack systems supporting quantum and fabrication engineers. Build scalable services, manage schemas and compatibility, improve performance and observability, and establish safe AI coding-agent frameworks. Collaborate directly with technical users, guide priorities, mentor engineers, and contribute across cloud infrastructure, scientific computing, and internal tooling.

Volunteer Senior Software Engineer contributing 8–20 hours/week to WeVote's React and Django codebases. Install and run repos (Mac/Unix), join 3–5 person teams, attend weekly meetings, complete intermediate-to-advanced projects, and support other volunteers to prepare systems for the 2026 elections.

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.

Design and build distributed manufacturing software coordinating state, timing, and behavior across hardware. Implement APIs, real-time controllers, instrumentation for ML/AI, and reliability/observability. Drive architecture decisions, improve CI/CD and testing practices, debug across software/firmware/hardware, and collaborate with cross-functional engineering teams to converge on a production-ready platform.

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.

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.

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.

Build and maintain websites, web applications, and mobile apps (iOS/Android). Implement front-end interfaces from designs using JavaScript/TypeScript, React, HTML/CSS, and Sass. Integrate with back-end APIs (GraphQL), optimize performance, run experiments to drive product decisions, and collaborate with designers and backend engineers. Keep current with new technologies.

Build and deploy LLM-powered features for clinical, patient, and operational workflows. Responsibilities include prompt design, retrieval, tool use, agent orchestration, evaluation harnesses, feedback loops, production operations, and AI engineering tooling. Partner with clinical, product, and safety stakeholders to ensure responsible healthcare-grade AI. Mentor teammates, communicate model behavior clearly, and stay current with emerging AI research and development practices.

Leads AI engineering strategy across clinical, patient, and operational products. Designs and operates production retrieval, orchestration, agentic, and evaluation systems, establishing standards for AI safety, observability, responsible deployment, and reliability. Partners with clinical, product, and executive leaders on the AI roadmap, mentors engineers, evaluates emerging models and tools, and codes regularly in Python.