Top Backend Developer Jobs

Build and ship backend features end-to-end using Ruby on Rails and SQL. Lead complex technical projects, solve architecture challenges, establish standards, conduct meaningful code reviews, resolve high-risk bugs, document systems, collaborate across engineering teams, and mentor junior engineers.

Design, build, deploy, and operate Philo’s scalable server-side ad insertion and programmatic advertising services. Develop resilient data pipelines, ad integrations, identity and measurement solutions, monitoring tools, and highly available microservices. Collaborate with ad ecosystem partners, video delivery, ad operations, data science, and business stakeholders to optimize ad delivery, reliability, performance, security, and compliance with industry standards.

In this role, you'll ensure the reliability and scalability of the NG-SIEM platform, manage incident responses, and collaborate across teams to enhance system performance.

Lead backend engineering for a high-performance, data-intensive SaaS platform. Responsibilities include defining technical vision, designing scalable and highly available systems, executing technical projects, participating in architecture decisions, monitoring and optimizing services, improving CI/CD and infrastructure, conducting postmortems, mentoring engineers, documenting practices, and aligning with partner teams.

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.

Designs and maintains scalable data platforms, backend services, APIs, ingestion pipelines, and data quality frameworks. Responsibilities include transforming heterogeneous datasets, supporting NLP and analytics workflows, modernizing legacy processing systems, monitoring pipeline reliability, and maintaining data lineage and documentation. The role also supports cloud-native architecture, governance, security compliance, and NIH Public Trust requirements.

Build and operate distributed cloud services for Microsoft Dataverse Runtime, enabling secure AI agents, copilots, workflows, and enterprise applications. Responsibilities include architecture, implementation, deployment, monitoring, incident response, reliability improvements, and operational excellence for highly available services. The engineer will partner across Azure, Power Platform, Dynamics 365, and AI teams, contribute to technical decisions, support production systems, use AI-assisted engineering tools, and mentor other engineers.

Designs, develops, and supports back-end applications, SQL Server databases, automated data pipelines, integrations, and data-processing systems. Builds reliable ETL workflows, optimizes database and application performance, troubleshoots production issues, and manages solutions through testing, deployment, monitoring, and support. Collaborates with developers, database administrators, analysts, and business partners while applying source control, automated testing, CI/CD, documentation, and secure release practices.

Build and own backend features for sign-in, authentication, authorization, entitlements, and subscription systems. Integrate product teams with identity services, contribute to highly available systems, participate in on-call and incident resolution, and address root causes. The role also includes code reviews, documentation, mentoring, responsible AI experimentation, and collaboration across a distributed organization.

Leads development of secure, scalable Python backend and AWS cloud-native applications using microservices, serverless, containers, and infrastructure as code. Designs distributed systems, APIs, data stores, CI/CD pipelines, observability, resiliency, and security controls. Troubleshoots production incidents, conducts root-cause analysis, optimizes performance, modernizes dependencies, promotes AI-assisted engineering practices, and mentors team members while collaborating with product, platform, SRE, security, and data teams.

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.

Own and evolve core procurement backend systems, including purchase orders, approvals, receiving, matching, accounting data, and ERP or supplier integrations. Design reliable data models and asynchronous workflows, build AI-assisted automation, guide technical direction, and collaborate with product, design, data, accounting, and Bill Pay teams. Mentor engineers and maintain system quality through design reviews, code reviews, monitoring, and iterative improvement.

Develop and support enterprise Java backend applications involving messaging and transaction processing. Responsibilities include architecture participation, hands-on coding, integration testing, production support, cloud application development, Agile requirements refinement, deployment, and mentoring junior developers. The role requires extensive Java/JEE, AWS, database, containerization, CI/CD, and software engineering experience, with hybrid work in Ashburn, Virginia and eligibility for a Public Trust position.

Design, build, and operate reliable UEM reporting pipelines supporting data ingestion, transformation, analytical storage, and reporting. Develop batch and streaming systems, optimize schemas and queries, troubleshoot performance and reliability issues, and implement observability and data validation. Collaborate across engineering, product, and security teams while owning features through deployment and production support.

Own and evolve core backend systems for Ramp’s Bill Pay product, including payment execution, invoice intake, approvals, accounting integrations, and AI-powered AP automation. Design reliable, traceable workflows across payment rails and ERPs, improve system performance and observability, and ensure correctness through retries, idempotency, and partial failures. Provide technical direction, participate in design and code reviews, and mentor engineers.

Design and deliver scalable AI and generative AI applications using LLMs, RAG, agentic frameworks, prompt engineering, evaluation, and fine-tuning. Build backend APIs, microservices, cloud-native systems, and frontend integrations using Angular or React. Lead architecture decisions, develop observability and evaluation tooling, ensure software quality and security, collaborate cross-functionally, and mentor engineers.

Build and operate a multi-cloud, multi-tenant platform for distributed LLM inference. Responsibilities include developing fault-tolerant services across cloud and hardware environments, improving observability and cold-start performance, and creating Helm charts and Kubernetes operators for scalable deployments. The role requires backend engineering, distributed systems, cloud infrastructure, Kubernetes, and machine learning experience.

Provide back-end development and KM/web development support to automate collection, organization, dissemination, visualization, and archival of USSTRATCOM J2 intelligence products. Improve digital production, business processes, dashboards, integrations, security on DoD classified networks, and train stakeholders while communicating with senior government and military officials.

Lead backend development for an AI platform, owning architecture, scalability, reliability, and performance of high-load services. Responsibilities include evolving an AI Gateway, designing orchestration pipelines, integrating AI models, improving observability and security, and supporting RAG, MCP, and agent capabilities. The role remains hands-on with coding, design reviews, troubleshooting, and mentoring while collaborating across engineering, infrastructure, QA, and product teams.

Develop and support Java backend applications involving messaging and transaction processing. Responsibilities include architecture participation, coding, integration testing, requirements refinement in Agile teams, production support, and deployment of fixes. The role requires cloud and serverless experience, NoSQL and SQL databases, Spring Boot, Docker, Kubernetes, CI/CD tooling, and enterprise Java technologies. This hybrid position requires two days weekly onsite in Ashburn, Virginia, U.S. citizenship, and the ability to obtain and maintain Public Trust suitability.

Own backend features from inception through production, develop and improve Kotlin services, write maintainable and well-tested code, and design scalable, reliable distributed systems within a small cross-functional team.

Build and operate the inference and orchestration backend powering AI interactions across mobile and desktop applications. Responsibilities include designing production AI services, optimizing latency and throughput, managing caching, batching and streaming, and maintaining monitoring, logging, alerting, and incident response systems. The role requires reliable APIs, distributed-systems debugging, and scalable integration with LLMs, embeddings, and multimodal models.

Build and scale backend services and cloud infrastructure for an AI-powered consumer platform. Responsibilities include developing Python or Go APIs, supporting AI/LLM workloads, designing asynchronous processing systems, managing AWS infrastructure with Infrastructure as Code, improving observability and CI/CD, troubleshooting production incidents, optimizing reliability and cloud costs, and enforcing security and disaster recovery practices.

Designs and scales high-performance backend web services and ETL pipelines supporting tens of thousands of transactions per second. Responsibilities include architecting fault-tolerant distributed systems, improving performance, developing monitoring and deployment strategies, collaborating across product and engineering teams, and supporting recruiting and onboarding. The role requires expertise in data-intensive systems, microservices, cloud architectures, and commercial SaaS products.

Build and evolve Uber One membership platforms supporting benefits, offers, savings, and engagement across UberEats and UberX. Design high-QPS, low-latency, highly available distributed systems and microservices used by millions globally. Lead technical strategy, architecture, API design, testing, monitoring, alerting, incident management, and end-to-end delivery while collaborating with engineers, product managers, data scientists, designers, and stakeholders.