Find remote programming jobs in Frontend, Backend, DevOps, QA, or as a FullStack or Data engineer. We curate the best remote software development jobs to match your area of expertise. Software Developers design, specify, create, and maintain web and native apps. Remote Software Engineer jobs where people telecommute (work remotely) are on the rise and we can help you to stay ahead of the curve.
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You will be responsible for ensuring and continuously improving technical software quality throughout the development lifecycle. This includes establishing company-wide code quality standards, managing CI/CD integration, and advising development teams on maintainability and technical excellence.
Architect end-to-end avionics software systems from concept through certification while leading development in compliance with DO-178C standards. Collaborate across multidisciplinary teams to support certification audits, requirements allocation, and technical leadership throughout the product lifecycle.
The Associate Applied AI Engineer will implement engineering solutions using AI-assisted coding tools within a cross-functional pod. They will also validate AI-generated code, perform basic testing, and collaborate with product leads to translate requirements into software.
Define the architectural vision for new products and platforms while driving technical strategy and Proof of Concept initiatives. Lead complex system designs, establish engineering standards, and mentor technical teams to ensure scalable, production-ready solutions.
Define and evolve the architectural vision for new products, platforms, and technology initiatives while driving Proof of Concept projects. Collaborate with engineering teams to design scalable, cloud-native solutions and establish architectural standards and best practices.
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You will actively build and manage sales operations in the UK and Scandinavia, positioning the company as a key brand in these markets. This involves identifying potential customers, conducting online sales meetings, and negotiating contracts while providing market insights to the development team.
Generate AI product images using internal workflows and overlay copy using Adobe Photoshop to match the brand's visual style. Manage creative assets and iterate on designs based on team feedback and ad performance data.
The AI Business Analyst will identify and manage business requirements for AI-based solutions while collaborating with stakeholders and developers to ensure successful delivery. They will also analyze business processes, create prototypes, and support the adoption and governance of AI initiatives.
You will lead the design of enterprise AI solutions and define architecture standards across the Microsoft ecosystem. This involves hands-on prototyping, guiding technical decisions, and collaborating with cross-functional teams to ensure scalable and secure AI adoption.
You will design, develop, and deploy enterprise AI solutions using Microsoft Copilot Studio, Azure, and modern AI engineering frameworks. The role involves building AI agents, implementing RAG architectures, and optimizing production-ready AI applications through continuous improvement.
Assist in building, testing, and deploying AI-powered solutions using Microsoft Copilot Studio, Power Platform, and Azure. Collaborate with stakeholders to configure AI agents, workflows, and integrations while maintaining technical documentation.
The Data Scientist will serve as the core technical expert for the Trust and Safety team, responsible for protecting the platform and evaluating healthcare claims. They will review billing patterns, identify data anomalies, and provide clear analytics to legal and compliance partners.
Design, develop, and maintain scalable backend services using Python while contributing to frontend React applications. Integrate AI capabilities into business solutions and manage the full software lifecycle from design to production support.
You will build and deploy end-to-end LLM-powered features, managing the entire lifecycle from development to production. Additionally, you will own answer quality by building evaluation datasets and debugging production systems using tracing and observability tools.
The Advanced Healthcare Implementation Engineer will design and deliver secure, scalable integrations between Solventum solutions and customer healthcare systems. They will also lead technical validation, troubleshooting, and go-live readiness activities to ensure successful operational transitions.
The Manual QA Engineer will validate new features, conduct smoke, sanity, and regression testing, and maintain test documentation. They will also collaborate with developers and product managers to investigate and report bugs throughout the development lifecycle.
You will perform manual testing of backend and frontend systems on mobile and web applications, including API, database, and regression testing. Additionally, you will create test documentation, investigate bugs, and act as a QA feature owner within a Scrum environment.
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You will own the end-to-end learner journey, focusing on discovery, enrollment, and the learning experience. Your primary goal is to drive learner retention and engagement through AI-native product features.
You will lead architectural and code-level performance engineering initiatives to optimize Elasticsearch for scale and predictability. This involves profiling system behavior, driving automation for benchmarking, and mentoring other engineers to foster a performance-first culture.
Lead architectural and code-level performance engineering initiatives to optimize Elasticsearch performance and predictability. Develop foundational performance models, drive automation for benchmarking, and mentor other engineers to foster a performance-aware development culture.
You will lead architectural and code-level performance engineering initiatives to optimize Elasticsearch for scale and predictability. This involves profiling system behavior, driving optimization strategies, and mentoring engineers to embed performance-first thinking across the organization.
You will lead architectural and code-level performance engineering initiatives to drive the continuous optimization and predictability of the Elasticsearch platform. This involves profiling system behavior, designing performance models, and mentoring other engineers to foster a culture of performance-aware development.
You will lead architectural and code-level performance engineering initiatives to drive the continuous optimization and predictability of Elasticsearch. This involves profiling system behavior, designing performance models, and mentoring other engineers to foster a performance-first development culture.
You will lead architectural and code-level performance engineering initiatives to optimize Elasticsearch for scale and predictability. This involves profiling system behavior, driving automation for benchmarking, and mentoring other engineers to foster a performance-first culture.
Lead architectural and code-level performance engineering initiatives to optimize Elasticsearch for scale and predictability. Collaborate across teams to embed performance-first thinking and develop AI-assisted tools for benchmarking and profiling.
Lead architectural and code-level performance engineering initiatives to drive the continuous optimization and predictability of Elasticsearch. Collaborate across teams to embed performance-first thinking and develop AI-assisted optimization tools for complex distributed systems.
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You will lead architectural and code-level performance engineering initiatives to optimize Elasticsearch for scale and predictability. This involves profiling system behavior, driving automation for benchmarking, and mentoring other engineers to foster a performance-first culture.
Design and develop enterprise applications using Java while integrating AI and machine learning solutions. Collaborate on technical analysis, software architecture, and digital transformation initiatives for public sector organizations.
You will train and evaluate AI models by documenting your professional workflows and providing nuanced feedback. Tasks involve writing detailed outlines of regular job processes, including steps, tools, and edge cases.
You will train and evaluate AI models by documenting detailed workflows and providing nuanced feedback based on your professional expertise. Tasks involve writing structured outlines of regular job processes and performing critical evaluation tasks.
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