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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The Senior Business Analyst will translate complex clinical and technical requirements into actionable specifications for an AI-driven patient health data summarization tool. They will collaborate with multidisciplinary teams to ensure clinical accuracy, data traceability, and effective integration into clinician workflows.
You will meet with existing and prospective clients to provide personalized retirement and financial planning services. You will also utilize company-provided tools and marketing resources to expand your business and collaborate with team members to improve professional practices.
You will lead the development of core AI infrastructure and integrate LLM-based features into a high-traffic social media platform. This role involves owning services end-to-end, from schema design and deployment to monitoring for performance and safety.
You will design and implement AI-optimized data platforms and end-to-end analytical solutions to solve complex business problems for clients. Additionally, you will act as a trusted advisor to stakeholders and lead small project teams to deliver scalable data engineering architectures.
The AI Systems Engineer will design, optimize, and deploy machine learning models for resource-constrained edge devices. This role involves implementing model compression and hardware-aware optimization to ensure reliable AI performance outside of data centers.
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The AI Governance Engineer will lead the design and implementation of security controls, threat models, and incident response capabilities for AI and machine learning systems. This role focuses on mitigating risks such as prompt injection, model abuse, and data exfiltration within LLMs and AI infrastructure.
The Automation Solutions Engineer will design, build, and maintain infrastructure-as-code foundations using Terraform. This role involves creating reusable modules, hardening pipelines, and standardizing infrastructure delivery across cloud environments.
The ML Data Engineer will build and operate large-scale data systems to support AI training and evaluation pipelines. Responsibilities include managing data ingestion, transformation, quality assurance, and high-throughput delivery for training jobs.
The Cybersecurity Engineer will embed security throughout the software development lifecycle by partnering with engineering teams to design secure systems. They will identify vulnerabilities and implement security improvements to reduce risk across the application portfolio.
Design, build, and operate the platform layer that powers large-scale AI training and inference workloads. Focus on GPU clusters, distributed training frameworks, scheduling, and storage performance while ensuring reliability and efficiency.
The Data Infrastructure Architect will define and lead the architecture of the enterprise data platform, covering ingestion, storage, processing, and governance. This role involves setting strategic standards for data modeling and collaborating with cross-functional teams to deliver a scalable data foundation.
The Lead Salesforce Architect will design and govern enterprise-level Salesforce implementations across multiple clouds. They will drive technical strategy, establish standards for security and integration, and collaborate with stakeholders to deliver scalable solutions.
The developer will design and build production-grade Salesforce solutions using Apex, Lightning Web Components, and Flow. They are responsible for delivering custom business logic, integrations, and automation while ensuring long-term maintainability.
The Reliability Monitoring Engineer will design and operate metrics, logging, tracing, and alerting platforms to ensure system reliability. This role involves managing the full observability stack, from collection agents to dashboards, while focusing on signal quality and operational efficiency.
The Site Reliability Engineer will ensure the availability, performance, and operational excellence of large-scale distributed systems. They will apply software engineering principles to infrastructure problems to push the platform toward higher reliability and lower operational toil.
The developer will build and maintain solutions across ITSM, ITOM, HRSD, CSM, and custom scoped applications. Responsibilities include hands-on configuration, scripting, integrations, and UI customization while ensuring platform performance and upgrade safety.
The role involves designing, developing, and maintaining integrations between Workday and the broader enterprise application landscape. You will collaborate with cross-functional partners to translate requirements into engineered solutions while providing mentorship and code reviews.
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The Field Service Engineer will install, maintain, and repair a diverse range of high-value analytical instruments to ensure peak performance. They will act as a company representative, delivering exceptional technical service and building strong relationships with customers.
The DevSecOps Engineer will assess and architect communication workflows across Salesforce, AWS, and VA Notify to ensure high-volume reliability. They will also build, test, and deploy integration components while automating security scanning within CI/CD pipelines.
The Data Engineering Tech Lead oversees the architecture, development, and maintenance of the data platform while serving as the primary subject matter expert. They collaborate with cross-functional teams to deliver complex applications, enforce architectural standards, and manage operational processes including crisis and change management.
The Senior Analyst is responsible for developing and maintaining profitability models to drive business growth and margin improvements. They will also leverage data analytics to identify profit opportunities and provide support to internal teams as a subject matter expert.
The Sr IT Integration Engineer is responsible for the design, development, and maintenance of mission-critical integrations between diverse IT systems. This role involves leading complex integration projects, troubleshooting data flow issues, and providing leadership through coaching and mentoring.
You will lead the development of detection capabilities and AI workflows to enhance Elastic Security's threat research and defense mechanisms. This involves investigating multidomain threat vectors and presenting findings to improve team knowledge and community awareness.
The Solutions Engineer acts as the technical owner of merchant relationships, managing the entire integration process from pre-sales discovery to post-launch support. They bridge the gap between business and technical teams by designing custom solutions, leading product demos, and troubleshooting complex integration issues.
Design and build large-scale offline ML experimentation platforms and production-grade training orchestration frameworks. Develop infrastructure for experiment tracking, model registries, and agentic AI execution platforms to support autonomous workflows.
You will own the connection between the design system and production code, ensuring they evolve together across iOS, Android, and Web. You will also collaborate with engineering and design teams to build scalable, accessible components and improve the overall design-to-code workflow.
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You will own hands-on quality assurance across web, mobile, and API platforms while building reliable test automation and infrastructure. Additionally, you will implement quality gates in CI/CD pipelines and use observability tools to investigate production failures and improve regression coverage.
Design and deploy offline 3D reconstruction, lane line detection, and mapping modules to generate high-quality annotations for autonomous vehicle sensor data. Lead technical projects, mentor team members, and define data governance standards to improve perception and mapping model performance.
Design, build, and ship mobile applications that integrate with connected devices, sensors, and cloud services. Collaborate with cross-functional teams and clients to ensure app performance, reliability, and security.
The role involves building and maintaining production-grade data pipelines to process petabytes of autonomous vehicle log data. You will collaborate with ML engineers to deploy tagging models and manage AWS infrastructure to support large-scale data processing.
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