Top Senior Level Software Engineer Jobs in Los Angeles, CA

Design Engineer will rapidly prototype and iterate mobile products (primarily iOS), build tooling and internal systems, collaborate with designers, PMs, and engineers to drive product strategy, test with researchers, and ship polished experiences to hundreds of millions of users. Role involves presenting work to leadership and occasionally prototyping on web, AR, and AI platforms.

Lead design and build of an AI-powered, spec-driven development platform: evaluate frameworks, architect end-to-end tooling, integrate with CI/CD and Kubernetes, partner with DevOps, MLE, and Security, instrument adoption and velocity metrics, and drive org-wide rollout and training to enable non-engineers to author specs.

Lead design and delivery of scalable budgeting and pacing infrastructure. Build and maintain high-performance Java production systems, collaborate with engineering and product teams, apply data-driven decision making, and ensure reliability, observability, and continuous improvement of distributed systems.

Design, build, and scale cloud-based backend platform components and connectors for ERPs, banks, payments, tax and subledger systems. Lead architecture, deliver highly available multi-tenant SaaS services (API gateway, event bus, identity, scheduler, search, workflow orchestration), ensure performance, security, extensibility and testability, mentor engineers, drive technical decisions, and support deployments and occasional off-hours support.

Lead and grow a software engineering team owning delivery, quality, and operational health. Provide technical oversight for architecture and code quality, drive planning and execution cadence, adopt AI-assisted development tooling, recruit and onboard engineers, remove blockers and manage cross-team dependencies, and partner with product and design to deliver high-impact work.

Design, build, and own backend services, APIs, and integrations supporting customer care workflows. The role connects Salesforce, billing, identity verification, document management, and iPaaS platforms; requires automated testing, code reviews, incident response, performance monitoring, and cross-functional collaboration. The engineer will also apply AI tools and may build production LLM solutions.

Design, build, deploy, and maintain resilient, scalable software for Toast Delivery Services. Develop real-time delivery tracking, driver matching, pricing, refunds, and payment-related systems. Solve distributed-systems and scaling challenges, integrate with partner APIs, uphold production reliability, promote strong engineering practices, and mentor teammates.

Define the technical vision and multi-quarter strategy for Coinbase’s FinHub financial infrastructure. Architect scalable ledger and money-movement primitives across fiat and crypto, ensuring double-entry accounting, idempotency, reconciliation, auditability, reliability, and safe failure recovery. Lead complex cross-team architectural initiatives, collaborate with finance, risk, compliance, and operations stakeholders, and mentor senior engineers while improving system design and operational excellence.

Build and optimize MongoDB’s SQL interface, including query engines, SQL-to-MQL translation, database connectors, and BI integrations. Develop backend systems that improve performance, scalability, reliability, and usability for large datasets and complex queries. Collaborate with product managers and customer experience teams, contribute to roadmap initiatives, resolve bugs, and lead major technical projects.

Leads architecture and hands-on development of scalable backend systems and APIs supporting real-time applications. Owns the engineering lifecycle, writes high-performance code, establishes testing and reliability practices, resolves production issues, guides technical roadmaps, collaborates cross-functionally, and mentors engineers. The role requires expertise in object-oriented backend development, distributed cloud systems, automated testing, system monitoring, and technical leadership.

Define architecture and metrics for autonomous driving evaluation, lead cross-functional integration across autonomy and simulation teams, develop statistical and machine learning methods, analyze large-scale time-series data, manage evaluation KPIs and release gates, and communicate safety and readiness insights through dashboards and stakeholder presentations.