Remote | Software Engineer, Platform Engineering — $200,000–$300,000/year

24-Mag•New York, NY

3d•Remote

About The Position

This is a full-time, fully remote software engineering opportunity focused on platform engineering, full-stack development, backend architecture, 0-to-1 product development, and AI-native software engineering. The engineer will own solutions from problem discovery and architectural design through implementation, deployment, and continuous improvement. The role combines hands-on development with product thinking, system design, technical decision-making, and AI-assisted engineering workflows. The opportunity is available through 24-MAG LLC, which connects experienced professionals with remote consulting opportunities.

Requirements

At least 4 years of professional software engineering experience.
Strong foundation in full-stack development and backend systems.
Demonstrated expertise in software architecture, system design, and production application development.
Experience building products from concept to launch in 0-to-1 engineering environments.
Strong understanding of backend architecture, API design, databases, data modelling, and software integrations.
Practical experience developing applications using modern programming languages, frameworks, and development tools.
Ability to design reliable, scalable, maintainable systems and evolve architecture as product requirements change.
Active experience using AI coding tools such as Cursor, Claude Code, or equivalent solutions in daily development workflows.
Strong product-oriented mindset and understanding of user requirements, business objectives, and product priorities.
Ability to make architectural and technical decisions independently while balancing engineering trade-offs.
Ability to translate ambiguous requirements into structured, production-ready software solutions.
Strong understanding of software engineering practices, testing, debugging, deployment, and iterative development.
Hands-on approach to technical problem-solving and efficient delivery of functional software.
Strong analytical reasoning, technical problem-solving, communication, and independent decision-making capabilities.
Ability to own engineering initiatives from planning through deployment and continuous improvement.

Nice To Haves

Experience as an early engineering team member at a startup or similarly fast-moving technology organisation.
Experience building AI-powered products, agentic workflows, or LLM-integrated applications.
Familiarity with internal platform development, developer tooling, or workflow automation systems.
Knowledge of cloud infrastructure, distributed systems, and scalable backend architectures.
Experience evolving technical systems through different stages of startup growth.
Previous collaboration with founders, product leadership, or cross-functional startup teams.

Responsibilities

Design and build software products from concept through production launch and subsequent iterations.
Translate business requirements, user needs, and ambiguous product ideas into practical engineering solutions.
Own product development across discovery, technical planning, implementation, and deployment.
Develop production-ready applications balancing functionality, usability, performance, and maintainability.
Apply iterative development practices to deliver product improvements and support business objectives.
Design scalable, reliable software systems using appropriate architectural patterns and engineering principles.
Develop and maintain backend services, APIs, databases, and integrations.
Make technical decisions involving architecture, data modelling, performance, and operational requirements.
Evaluate trade-offs involving implementation speed, simplicity, reliability, and long-term scalability.
Improve existing systems to meet evolving product requirements and operational demands.
Build and enhance internal platforms, developer tools, applications, and supporting infrastructure.
Implement functionality across frontend, backend, and integration layers.
Develop systems and workflows that improve operational efficiency and support business processes.
Integrate internal services, external APIs, databases, and software components.
Maintain code quality, system performance, and reliability in production environments.
Use AI-powered development tools to accelerate implementation, debugging, testing, and technical problem-solving.
Incorporate AI coding assistants such as Cursor or Claude Code into daily engineering workflows.
Develop and enhance AI-powered applications, internal automation tools, and intelligent software workflows.
Evaluate opportunities to integrate AI capabilities into products, platforms, and operational processes.
Validate AI-assisted implementations and maintain software quality.
Collaborate with product, design, and operations stakeholders to define requirements and priorities.
Contribute technical expertise to product decisions, architectural planning, and engineering strategy.
Identify solutions to technical challenges and independently drive implementation.
Use feedback, operational needs, and product performance to guide continuous improvement.
Take end-to-end ownership of engineering deliverables and support efficient development and deployment.