Top Hybrid Software Engineer Jobs

Develop next-gen ad formats and backend solutions, advocate best practices, influence company-wide technical direction, mentor, and collaborate across teams.

As a Backend Engineer, you'll design and implement scalable services, collaborate across teams, and maintain high availability and operational excellence.

The Principal Software Engineer will design and scale engineering components, lead projects, advocate best practices, and influence technical direction across teams.

Maintain and develop production IT applications and integrations (MES-to-ERP/SAP), manage Windows Server and MS SQL environments, build Power Apps/Power Automate solutions, create Power BI dashboards and complex SQL queries, and support label/printing and barcode integrations for manufacturing operations.

As a Senior Software Engineer, build and support decisioning platforms, ensure AML compliance, and mentor junior developers while developing both front-end and back-end applications.

As a Software Engineer, you'll develop features for loan products, ensuring code quality and system improvements, while working closely with various teams.

Develop backend applications in a cloud-based microservice architecture, participating in technical architecture and delivering scalable services.

The role involves creating architecture solutions for various platforms, guiding product-related architecture, managing tech debt, and mentoring teams, while ensuring standards and practices are met.

The Solutions Engineer will act as a technical expert for partner integrations, provide guidance on data solutions, and collaborate with various internal teams to enhance product and service offerings in the programmatic advertising space.

Develop software applications for GM's Motorsports IT team, focusing on web apps, cloud infrastructure, and mentoring developers. Requires expertise in various technologies and software development methodologies.

The Software Engineer will design, build, and maintain scalable, cloud-native applications with AI/ML capabilities, collaborating with cross-functional teams and owning features throughout the software development lifecycle.

The Senior ML Infrastructure Engineer will design, implement, and optimize computing platforms for simulation workflows, ensuring high reliability and performance. Responsibilities include leading technical decisions, collaborating with ML engineers, and enhancing system efficiency.

Lead the architecture interface between Product and Engineering, design end-to-end solutions for ad systems, and mentor teams. Responsible for establishing technological standards and reducing technical debt.

Lead and manage software engineering teams to deliver secure, scalable, well-tested cloud applications. Drive architecture, agile delivery, backlog prioritization, mentorship, hiring, and cross-functional collaboration to meet business objectives and maintain product stability.

As a Lead Software Engineer, you will develop and deploy Generative AI solutions using Python, manage CI/CD processes, and collaborate on AI project architectures and implementations.

Early-career application developers will assist in designing, developing, testing, and maintaining internal business applications, work within existing codebases, participate in Agile team ceremonies, troubleshoot and fix bugs, monitor performance, and produce basic documentation while collaborating with stakeholders and senior developers.

Join small Agile teams to design, develop, test, and maintain back-office applications. Contribute to existing codebases, troubleshoot issues, support bug fixes, monitor performance, and produce basic documentation while learning from senior developers.

Early-career developers will assist in designing, developing, testing, and maintaining internal business applications, troubleshoot and monitor performance, contribute incremental features, participate in Agile team ceremonies, and prepare basic documentation.

Lead design and implementation of high-performance, scalable frontend systems and shared component libraries for Zocdoc Search. Integrate LLMs, embeddings, and ranking signals into intuitive, accessible search interfaces, optimize React/GraphQL flows for low latency, and mentor engineers while driving architectural direction and observability.