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As of Aug 22, 2026, the average hourly pay for weekday rust programming in the United States is $30.96, according to ZipRecruiter salary data. Most workers in this role earn between $25.48 and $34.86 per hour, depending on experience, location, and employer.

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States with the most job openings for Weekday Rust Programming jobs include:

Onsite | Senior Full Stack Software Engineer $85-$105/hour

24-MAG LLC

Manhattan, NY • On-site

$85 - $105/hr

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Senior Full-Stack Software EngineerWe are sharing a specialised full-time consulting opportunity for senior full-stack software engineers with extensive production experience building and shipping complex applications, services, and systems across modern backend, frontend, data, and cloud environments. This role supports an advanced generative AI initiative focused on building, integrating, and stress-testing real software using frontier AI models. Selected engineers will develop production-quality applications and internal tools, integrate pre-release model APIs, diagnose model and integration failures, and deliver working software rapidly across evolving technical requirements.Key ResponsibilitiesBuild and ship full-stack applications, backend services, APIs, and internal engineering toolsDevelop production software using Python, Java, Rust, C#, C++, TypeScript, or related technologiesWork across backend architecture, frontend applications, data models, and cloud environmentsOwn technical implementation from initial design through deployment and operational useDeliver robust, maintainable code under fast-moving project requirementsIntegrate pre-release AI model APIs into working software applicationsBuild supporting tool interfaces, evaluation harnesses, and application scaffoldingDevelop telemetry and instrumentation to observe model and system behaviourTest model capabilities within realistic end-to-end software workflowsIdentify integration constraints and technical limitations during implementationDiagnose model, application, and integration failure modes surfaced during developmentInvestigate unexpected behaviours, implementation issues, and system-level problemsTranslate engineering observations into clear written technical feedbackDocument reproducible failures and relevant technical contextProvide actionable findings to research and engineering stakeholdersPrototype solutions quickly against evolving or incomplete specificationsOnboard onto unfamiliar codebases and contribute working code with minimal ramp-upDeliver functional increments while requirements continue to evolveCollaborate with engineering leadership and other developers on architecture and implementation decisionsMaintain strong standards for code quality, technical documentation, and system designIdeal ProfileStrong candidates may have:At least 6 years of dedicated professional software engineering experienceSignificant experience building and shipping production software within sophisticated engineering environmentsEnd-to-end ownership of production systems or applicationsDeep production expertise in at least one of Python, Java, Rust, C#, or C++Demonstrated professional delivery in a second programming language or technical ecosystemHands-on experience with backend services and API designExperience with React or another modern frontend frameworkStrong understanding of data modelling and application architectureExperience deploying and operating software in cloud environmentsProven ability to learn unfamiliar codebases and deliver quicklyDemonstrable professional progression and increasing technical responsibilityStrong written communication and ability to explain complex engineering decisions clearlyReliable weekday availability for approximately 40 hours per weekEducational BackgroundA degree in computer science, software engineering, computer engineering, or a related technical discipline may be highly relevantAdvanced technical education may strengthen an applicationEquivalent senior-level professional software engineering experience may also be consideredSubstantial hands-on production engineering experience is particularly important for this engagementNice to HaveProfessional expertise across multiple programming-language ecosystemsStrong Python, Java, Rust, C#, C++, or TypeScript experienceExperience building AI-powered applications or developer toolsFamiliarity with LLM or foundation-model APIsExperience developing evaluation harnesses or technical benchmarking infrastructureBackground building internal engineering platforms or developer toolingStrong cloud architecture and production operations experienceExperience with observability, telemetry, and system instrumentationBackground working in fast-moving research or advanced technology environmentsWhy This OpportunityBuild production-quality software around frontier AI systemsWork across backend, frontend, data, cloud, and model-integration workflowsTest advanced AI capabilities through realistic software applicationsIdentify technical limitations before new model capabilities reach broader deploymentCollaborate closely with experienced engineering and research teamsTake ownership of complex systems from implementation through deliveryContribute full-time to technically demanding, rapidly evolving projectsContract DetailsFull-time W-2 contingent employment opportunityExpected commitment of approximately 40 hours per week during weekdaysCompetitive rates between $85–$105 per hour depending on experience and project scopeWork may include full-stack application development, API integration, model testing, engineering tooling, debugging, and technical documentationCandidates should have deep production experience in at least one of Python, Java, Rust, C#, or C++, together with demonstrated delivery experience in a second technical ecosystemProjects and responsibilities may evolve according to research and engineering requirementsThis opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.