Top Remote Python Jobs

Develop and mature the LLDB-based Mojo debugger, including interactive debugging, IDE integration, debug information, expression evaluation, GPU debugging, profiling, and MCP capabilities. Define the debugger roadmap, collaborate with compiler and developer relations teams, engage the developer community, and support open-source contributions. The role requires LLDB internals expertise and strong knowledge of debuggers, linkers, compilers, and systems programming.

The role involves designing, developing, and maintaining software applications. Collaboration with cross-functional teams is expected, alongside optimizing existing systems.

Lead the Methods and Insights engineering teams, overseeing hiring, coaching, performance management, delivery, operational health, architecture, and developer experience. Partner with product leaders and founders to sequence work, manage risk, improve engineering processes, and ship reliable systems. Build AI-agent development practices, shared components, CI gates, conventions, and harnesses that help engineers move quickly while maintaining quality.

Build and shape front-end web applications for a rapidly growing B2B2C SaaS parking platform. Make architectural and design decisions, improve user experience, contribute productively with AI assistance, and help establish engineering practices in a startup environment. The role requires strong commercial front-end experience and collaboration with engineering leadership. Remote work is available, but occasional travel to San Francisco is required.

Teaches undergraduate and graduate software development courses online, develops syllabi and course materials, facilitates discussions, evaluates student work, provides feedback, and integrates responsible AI use into instruction. The role requires software development expertise, course preparation, assessment design, and ongoing faculty development. Candidates need a doctorate and substantial applied experience in software development or related computing disciplines.

Four-month, fully remote software engineering internship embedded within Wikimedia Foundation engineering teams. Interns complete a primary project with defined deliverables while learning through mentorship and hands-on work across mobile applications, editing tools, data platforms, release engineering, cloud infrastructure, observability, and contributor connection systems. The program requires 40 hours per week, independent problem-solving, collaborative communication, and foundational programming, database, scripting, and potentially SQL, Linux, networking, operating systems, or distributed-systems knowledge.

Designs and develops enterprise Appian solutions for DoD programs, including process models, integrations, ETL workflows, database structures, security controls, and ATO support. Translates stakeholder requirements into technical designs, troubleshoots complex issues, participates in Agile ceremonies, conducts reviews, presents solutions, and mentors junior developers. The role also leverages Appian AI/ML capabilities and supports secure, compliant digital engineering environments.

Leads software engineering for administrative and reporting tools, overseeing web and service integration architecture, development practices, scalability, testing, and production transitions. Designs full-stack solutions using Java EE and Angular, tunes SQL performance, manages feature delivery, and collaborates with UX/UI, product, architecture, and development teams. Coaches and trains full-stack developers while communicating technical solutions to stakeholders.

Lead the PayIn engineering organization responsible for payment acceptance, recurring billing, funding, transfers, reconciliation, processor integrations, and payment intelligence. Build and retain a high-performing team, scale reliable backend systems, establish SLOs and observability, improve release safety, and partner with Product, AI, and Risk Engineering. The role requires deep payments expertise, strong backend and distributed-systems experience, and the judgment to make technical and people decisions for business-critical services.

Leads data engineering teams while designing and optimizing scalable batch and real-time data pipelines on cloud platforms. Responsibilities include developing PySpark and Spark workflows, orchestrating Airflow DAGs, managing cloud infrastructure, implementing CI/CD, improving data quality and performance, and mentoring engineers. The role collaborates with clients, product, architecture, and program management teams, while applying generative AI and DevOps practices to improve engineering productivity and operational efficiency.