Onsite | Senior Full Stack Software Engineer — $85–$105/hour
Summary
Senior full-stack engineers build and ship production applications, integrate frontier AI models, and diagnose integration failures using Python, Java, Rust, C#, C++, or TypeScript.
We 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 Responsibilities
Full-Stack Software Development
- Build and ship full-stack applications, backend services, APIs, and internal engineering tools
- Develop production software using Python, Java, Rust, C#, C++, TypeScript, or related technologies
- Work across backend architecture, frontend applications, data models, and cloud environments
- Own technical implementation from initial design through deployment and operational use
- Deliver robust, maintainable code under fast-moving project requirements
AI Model & API Integration
- Integrate pre-release AI model APIs into working software applications
- Build supporting tool interfaces, evaluation harnesses, and application scaffolding
- Develop telemetry and instrumentation to observe model and system behaviour
- Test model capabilities within realistic end-to-end software workflows
- Identify integration constraints and technical limitations during implementation
Engineering Analysis & Failure Diagnosis
- Diagnose model, application, and integration failure modes surfaced during development
- Investigate unexpected behaviours, implementation issues, and system-level problems
- Translate engineering observations into clear written technical feedback
- Document reproducible failures and relevant technical context
- Provide actionable findings to research and engineering stakeholders
Rapid Prototyping & Technical Delivery
- Prototype solutions quickly against evolving or incomplete specifications
- Onboard onto unfamiliar codebases and contribute working code with minimal ramp-up
- Deliver functional increments while requirements continue to evolve
- Collaborate with engineering leadership and other developers on architecture and implementation decisions
- Maintain strong standards for code quality, technical documentation, and system design
Ideal Profile
Strong candidates may have:
- At least 6 years of dedicated professional software engineering experience
- Significant experience building and shipping production software within sophisticated engineering environments
- End-to-end ownership of production systems or applications
- Deep production expertise in at least one of Python, Java, Rust, C#, or C++
- Demonstrated professional delivery in a second programming language or technical ecosystem
- Hands-on experience with backend services and API design
- Experience with React or another modern frontend framework
- Strong understanding of data modelling and application architecture
- Experience deploying and operating software in cloud environments
- Proven ability to learn unfamiliar codebases and deliver quickly
- Demonstrable professional progression and increasing technical responsibility
- Strong written communication and ability to explain complex engineering decisions clearly
- Reliable weekday availability for approximately 40 hours per week
Educational Background
- A degree in computer science, software engineering, computer engineering, or a related technical discipline may be highly relevant
- Advanced technical education may strengthen an application
- Equivalent senior-level professional software engineering experience may also be considered
- Substantial hands-on production engineering experience is particularly important for this engagement
Nice to Have
- Professional expertise across multiple programming-language ecosystems
- Strong Python, Java, Rust, C#, C++, or TypeScript experience
- Experience building AI-powered applications or developer tools
- Familiarity with LLM or foundation-model APIs
- Experience developing evaluation harnesses or technical benchmarking infrastructure
- Background building internal engineering platforms or developer tooling
- Strong cloud architecture and production operations experience
- Experience with observability, telemetry, and system instrumentation
- Background working in fast-moving research or advanced technology environments
Why This Opportunity
- Build production-quality software around frontier AI systems
- Work across backend, frontend, data, cloud, and model-integration workflows
- Test advanced AI capabilities through realistic software applications
- Identify technical limitations before new model capabilities reach broader deployment
- Collaborate closely with experienced engineering and research teams
- Take ownership of complex systems from implementation through delivery
- Contribute full-time to technically demanding, rapidly evolving projects
Contract Details
- Full-time W-2 contingent employment opportunity
- Expected commitment of approximately 40 hours per week during weekdays
- Competitive rates between $85–$105 per hour depending on experience and project scope
- Work may include full-stack application development, API integration, model testing, engineering tooling, debugging, and technical documentation
- Candidates 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 ecosystem
- Projects and responsibilities may evolve according to research and engineering requirements
About the Platform
This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.
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