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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Own and scale the connector ecosystem by prioritizing and managing third-party API and app integrations for AI features. Collaborate with engineering teams to define product requirements, evaluate performance, and drive the roadmap for AI-powered tools.
Design and build scalable, secure microservices and APIs while integrating business databases with advanced AI engines. Optimize backend service latency for real-time AI model hosting and collaborate with AI engineers to deploy solutions in Docker environments.
You will own, build, and scale your own startup within the HealthTech sector while receiving intensive coaching and support. You will iterate your product to achieve product-market-fit and receive assistance in building sales and marketing operations.
You will own, build, and scale your own startup in the field of Artificial Intelligence while receiving intensive coaching and support. You will iterate your product to achieve product-market fit and build out your own sales and marketing functions.
You will own, build, and scale your own startup in the Applied AI sector while receiving intensive coaching and support. You will iterate your product to achieve product-market fit and build essential sales and marketing functions.
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Design and build scalable data pipelines to process bid stream, impression, and revenue data from programmatic sources. Develop ETL/ELT workflows and maintain data warehouses optimized for ad-tech query patterns.
Develop and maintain high-quality iOS applications while ensuring optimal performance, scalability, and user experience. Collaborate with cross-functional teams to design, launch new features, and implement robust CI/CD deployment processes.
You will build, maintain, and scale data scrapers and pipelines to collect financial data from various third-party sources. Additionally, you will perform technical investigations, conduct code reviews, and contribute to architectural improvements to reduce technical debt.
You will be responsible for planning, executing, and optimizing end-to-end CRM campaigns across multiple channels to drive player engagement and retention. This involves leveraging data insights for segmentation and collaborating with cross-functional teams to align campaigns with business objectives.
The DevOps Engineer will manage and automate AWS database infrastructure using Terraform and CI/CD pipelines while serving as an escalation point for troubleshooting. They will also build incident-response tooling and maintain documentation to improve operational efficiency and system reliability.
The Data Engineer will own and deliver data engineering tasks, integrations, and marketing systems while troubleshooting pipeline and data quality issues. They will collaborate cross-functionally to transform data across various platforms and support payment orchestration flows.
You will design, implement, and operate scalable AI agents and content generation pipelines to deliver measurable business value. Additionally, you will build evaluation frameworks and ensure production-grade reliability for customer-facing AI systems.
You will own and execute outbound campaigns for US-based clients by building Clay workflows and AI-powered automations. Additionally, you will manage client communication, test campaign performance, and optimize targeting strategies.
Monitor, troubleshoot, and maintain production automation workflows while ensuring system reliability. Develop new AI-powered solutions using LLMs and assist senior engineers with Python-based projects.
You will rebuild the AI content generation pipeline into a scalable multi-agent architecture and bring customer-facing RAG agents to production-grade reliability. Additionally, you will design analytics for the customer journey and build evaluation frameworks to measure AI agent performance.
Monitor, troubleshoot, and maintain production automation workflows while ensuring system reliability. Develop new AI-powered solutions using LLMs and assist senior engineers with Python-based projects.
Monitor, troubleshoot, and maintain production automation workflows while ensuring system reliability. Develop new AI-powered solutions using LLMs and assist in building internal automation projects.
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You will rebuild and scale AI content generation pipelines and production-grade RAG agents while integrating complex data sources. Additionally, you will design private AI environments and build evaluation frameworks to ensure high performance and reliability across the AI ecosystem.
You will embed with client teams to design and build production-grade AI systems, acting as the primary technical point of contact. You will also lead architecture reviews, mentor engineers, and contribute to the company's internal blueprint library.
Design, implement, and scale production-grade data pipelines and real-time streams ranging from megabytes to petabytes. Lead technical projects through architecture and implementation while collaborating with cross-functional teams to maintain data quality.
Develop and optimize ML models from scratch while collaborating with cross-functional teams to deploy them into production. Establish experimentation roadmaps and maintain reproducible pipelines to ensure optimal model performance.
Own and drive the quality, reliability, and evolution of production AI systems, including the delivery of major AI features. Design and orchestrate agentic, tool-using AI workflows and manage prompt engineering and experimentation pipelines.
Lead the design and development of shared libraries, Spring Boot starters, and agentic frameworks to enable internal teams to build AI agents. Mentor product teams in Python-based AI development and establish standards for agent orchestration, evaluation, and guardrails.
The Tech Lead is responsible for the technical direction, architecture, and engineering quality within their domain. They align technical decisions with business priorities while mentoring engineers and improving platform stability.
Design, develop, and maintain scalable high-performance applications using Elixir and related technologies. Lead architectural discussions, mentor junior engineers, and implement complex domain logic and data pipelines.
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Lead the design, deployment, and maintenance of robust cloud infrastructure primarily on AWS. Manage and develop engineering talent while aligning technical strategies with business outcomes and client needs.
Design and build production-grade AI systems, including RAG pipelines and agentic workflows, using Python and AWS. Own backend services and data pipelines end-to-end while translating client requirements into technical delivery plans.
Produce 15-20 high-performing AI-driven short-form ads per week for Meta using advanced AI tools. Lead and manage a team of editors, overseeing quality control, KPIs, and hiring/firing processes.
The candidate will be responsible for designing and maintaining data pipelines as a Senior Data Engineer. They will ensure the efficient flow and processing of data across the organization.
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