Top Backend Engineer Jobs in San Francisco, CA

As a Backend/AI Engineer, you'll integrate LLMs, optimize document processing pipelines, and improve API design for document understanding tasks.

Founding backend engineer responsible for prototyping and productionizing AI-powered systems for mainframe and COBOL modernization. The role includes shipping agentic features end to end, establishing testing and reliability standards, translating ambiguous problems into working systems, and leading architecture and technical direction with the CTO. The engineer will collaborate with enterprise customers and subject matter experts across multiple industries.

Own the reliability and architecture of Speak’s subscription payment systems across Paddle, RevenueCat, Stripe, and mobile app stores. Build provider integrations, ensure idempotent webhooks and reconciliation, implement monitoring and runbooks, lead incident response, and establish payment engineering standards. Partner with growth, product, finance, and support on monetization and reporting while mentoring engineers and defining the payments roadmap.

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.

Lead technical vision and strategy for Affirm’s Cards backend engineering organization. Architect scalable and reliable platforms, guide cross-team initiatives, champion AI adoption and engineering excellence, influence technical roadmaps, and mentor engineers through Staff level. The role requires strong architectural expertise, organizational leadership, project management, communication, and cross-functional collaboration.

Own and deliver backend lakehouse infrastructure goals, lead engineers through complex problems, and build highly available distributed data systems. Collaborate with product, design, analytics, and engineering stakeholders; define scalable technical solutions; improve code quality and engineering standards; monitor operational health; support on-call responsibilities; and mentor team members.

Build and maintain server-side software for a production product, owning projects from concept through launch. Develop scalable backend components, contribute to a new product area, improve code review and developer tooling, and enhance automated build and deployment pipelines. Collaborate closely with senior staff and executives in an on-site, autonomous team while maintaining dependable and responsive systems.

Build, test, release, and operate backend services from initial design through production. Lead sizable engineering projects, develop test environments, respond to incidents, monitor reliability, expand job orchestration and AWS cloud infrastructure, and design scalable distributed systems. The role also involves mentoring junior engineers and may include browser automation or LLM-based agent work.

Own and architect large-scale backend systems powering Anthropic’s API, Claude products, and enterprise platforms. Lead complex projects, make scalability and reliability decisions, collaborate across engineering, product, research, and commercial teams, and remain hands-on with code and AI models. Potential areas include platform serving, developer experience, agentic systems, identity, enterprise foundations, safety, and cloud-native distribution.

Design, implement, operate, and scale critical backend services such as identity, social graph, and persistence systems. Collaborate across teams to deliver product solutions, test and debug code, and apply best practices for availability, scalability, security, operational excellence, and cost management. Independently deliver medium-sized features, support incident resolution, and use AI tools responsibly to improve development workflows while maintaining production-quality standards.

Own the architecture, roadmap, and production operation of GridCARE’s AWS-based data platform. Design ingestion, data models, storage, compute, APIs, distributed processing, governance, observability, and reliable serving layers for energy data. Build and operate AI coding agent teams, establish platform standards, mentor engineers, and partner with product and domain experts. The role requires hands-on backend, distributed systems, data infrastructure, ETL/ELT, AWS, and technical leadership experience.

Own backend systems for a consumer application, building customer-facing features and solving data-focused problems such as user pairing and fraud prevention. Improve engineering workflows, testing tools, deployment automation, and release velocity. Independently lead projects from concept to completion while increasing backend ownership within a fast-growing company.

Own and build core backend services and infrastructure for sandboxed workloads, gateways, and task orchestration. Design production systems from zero to one, scale services, ship customer-facing features quickly, and make autonomous technical decisions. The engineer will gradually assume backend ownership from a senior engineer while collaborating closely with customers and the team.

Build and operate Python backend services for Oort, Loft Orbital’s mission lifecycle platform. Design APIs, integrations, and database interactions that connect infrastructure data and tools across teams. Collaborate with program management, satellite engineering, operations, and business stakeholders to translate complex processes into reliable software. Own features from design through production, apply a product mindset, incorporate user feedback, and reduce workflow complexity.

The Software Engineer will develop vertical workflows, implement scalable service architectures, ensure production-grade systems, evaluate AI performance, and collaborate cross-functionally to enhance engineering efficiency with AI tools.

Build and own high-volume backend services for automated jobs, including scheduling, queues, retries, and third-party integrations. Design scalable infrastructure, maintain data integrity and uptime, manage production performance, and deliver features from scoping through deployment. The role involves shaping platform architecture, handling heavy traffic, and collaborating closely with the technical lead. Candidates need startup experience, large-scale background processing expertise, Effect or functional TypeScript experience, and the ability to work hybrid in San Francisco.

Develop and maintain scalable backend services, collaborate on feature development, lead and mentor junior developers, ensure code quality and automation, and troubleshoot production issues in a fintech startup environment.

Lead fraud decisioning engineering initiatives by architecting, building, launching, and maintaining complex backend systems. Drive cross-functional projects from definition through monitoring, write high-quality and resilient code, review technical work, mentor engineers, collaborate with Product, ML, Analytics, and Business teams, and contribute to hiring and interview design.

Develop backend tools and systems that improve batch development, testing, workflow efficiency, and reliability. Collaborate with product, infrastructure, design, and analytics teams; break projects into deliverable phases; build scalable, well-tested code; monitor metrics; support system availability and on-call operations; debug code; conduct reviews; and contribute to engineering growth and hiring activities.

Design, deploy, and optimize Philo’s distributed video streaming infrastructure, including ingest, transcoding, packaging, delivery, RESTful services, analytics pipelines, DRM, and ad insertion. Improve platform reliability, performance, latency, security, video quality, and cost efficiency. Collaborate with content partners and internal video, advertising, client, and data teams while supporting streaming quality across new platforms. The role also involves architectural ownership, cloud operations, and mentoring.

Design and maintain scalable backend systems in a distributed microservices architecture. Build RESTful APIs, integrate third-party vendors, optimize SQL and NoSQL databases, and implement messaging, observability, CI/CD, and cloud infrastructure practices. Lead engineering initiatives from requirements through delivery, contribute to technical strategy, document systems, and improve reliability, performance, and scalability across user-facing applications.

Build and operate reliable backend services and financial systems supporting billing, payments, payer integrations, and revenue workflows. Design APIs, data models, durable workflows, and observability practices while ensuring correctness, security, and scalability. Collaborate cross-functionally, support production systems through on-call rotations, mentor engineers, improve developer tooling, and integrate AI technologies into engineering and operational processes.

Own the backend platform powering Vibecoderz, designing FastAPI microservices, Firestore schemas, Neo4j integrations, asynchronous workflows, secure APIs, and scalable Cloud Run deployments. Integrate Stripe and SendGrid, build CI/CD and automated tests, implement observability, and optimize services for 100K+ concurrent learners with sub-100ms latency. Collaborate with frontend, AI, DevOps, and product teams on system contracts, architecture, reliability, and performance.

Own backend product features end to end, from understanding enterprise marketing customer needs through design, development, delivery, and post-launch support. Collaborate directly with customers, shape product vision, build scalable services in Go, resolve bugs, and ensure features integrate seamlessly across the platform. The role requires strong product judgment, attention to detail, customer empathy, and ownership in a fast-paced startup environment.

Build and improve backend product capabilities for data cataloging, agent benchmarking, and workflow automation. Own features from user problem definition through design, implementation, launch, and production support. Develop APIs, services, data models, and workflow systems; investigate performance and production issues; contribute to architecture and code quality; and collaborate with Product, Design, and Engineering. The role is hybrid, requiring at least three days weekly in San Francisco or New York City.