We are sharing a specialised full-time opportunity for senior software engineers with substantial professional experience building and shipping production systems, deep technical expertise, and ownership of complex engineering decisions.

This role supports advanced research focused on improving how AI systems reason through real-world software engineering work. Selected professionals will review complex engineering tasks and outputs, develop authoritative reference solutions and instructions, and translate practical engineering judgement into rigorous standards for technically correct, production-quality problem solving.

Key Responsibilities

Software Engineering Quality Review

• Evaluate engineering tasks and technical outputs for correctness, completeness, and production realism
• Identify subtle implementation errors, unhandled edge cases, weak assumptions, and incomplete reasoning
• Review code that may execute successfully but produce incorrect or unreliable behaviour
• Assess whether proposed solutions would withstand professional code review
• Apply senior engineering judgement across complex technical scenarios

Systems & Backend Engineering

• Develop and review tasks involving backend services, distributed systems, and infrastructure
• Evaluate architecture, reliability, scalability, concurrency, and failure-handling decisions
• Assess trade-offs involving performance, consistency, availability, and maintainability
• Identify weaknesses in system design and implementation approaches
• Produce reference solutions grounded in real production engineering practices

Security & Cryptography

• Review engineering scenarios involving application security, systems security, and cryptographic concepts
• Evaluate security assumptions, threat models, and implementation decisions
• Identify vulnerabilities, unsafe patterns, and incomplete defensive reasoning
• Assess whether proposed security controls appropriately address identified risks
• Apply practical engineering standards to security-sensitive software problems

Embedded Systems & Firmware

• Develop and evaluate tasks involving embedded software, firmware, and hardware-constrained systems
• Review low-level implementation choices, interfaces, timing considerations, and resource constraints
• Assess reliability and correctness within constrained environments
• Identify edge cases involving hardware interaction and system state
• Apply practical understanding of embedded engineering workflows

Machine Learning Systems

• Review tasks involving machine learning infrastructure and production ML systems
• Evaluate data, model-serving, training, inference, and systems-integration decisions
• Assess engineering trade-offs around performance, scalability, reliability, and reproducibility
• Identify gaps between experimental implementations and production-ready systems
• Develop technically rigorous reference approaches to ML engineering problems

Developer Tooling & Platform Engineering

• Create and review scenarios involving developer platforms, internal tooling, CI/CD, and engineering productivity
• Evaluate system interfaces, automation, observability, and operational workflows
• Assess design decisions affecting developer experience and platform reliability
• Identify missing operational considerations and failure modes
• Apply practical platform-engineering judgement to complex workflows

Quality & Test Engineering

• Develop tasks involving test strategy, verification, reliability, and software quality
• Evaluate whether testing approaches adequately cover functional behaviour and edge cases
• Identify gaps in test coverage and validation methodology
• Review debugging and defect-analysis workflows
• Define what constitutes robust and production-ready engineering output

Instruction & Reference Solution Development

• Write detailed task instructions reflecting authentic engineering workflows
• Produce high-quality reference solutions to complex software problems
• Define what constitutes a complete, technically sound, and professionally credible response
• Translate tacit engineering judgement into explicit evaluation criteria
• Develop new tasks based on realistic engineering and system-design decisions

Quality Standards & Calibration

• Collaborate with research teams and specialists from adjacent technical domains
• Help maintain consistent standards across engineering-related evaluation work
• Identify recurring weaknesses and failure patterns in technical outputs
• Refine evaluation criteria based on observed performance
• Contribute domain expertise to new software and engineering research workflows

Ideal Profile

• Bachelor's degree or higher in Computer Science, Software Engineering, or a closely related engineering discipline
• Master's degree or PhD is strongly preferred
• 4+ years of substantive professional engineering experience building and shipping production software or engineered systems
• Genuine specialisation in at least one area such as:
  • Distributed systems and backend infrastructure
  • Security and cryptography
  • Embedded systems and firmware
  • Machine learning systems
  • Developer tooling and platform engineering
  • Quality and test engineering
• Clear progression into senior responsibility, such as Senior Engineer, Staff Engineer, Principal Engineer, Architect, Engineering Lead, or comparable level
• Demonstrated ownership of significant systems, architectures, or technical design decisions
• Shipped systems, granted patents, open-source contributions, or published technical work are highly valued
• Practical experience using large language models in professional engineering workflows
• Strong judgement when distinguishing technically rigorous solutions from superficially plausible ones
• Excellent written communication and ability to provide precise, structured technical feedback

Engagement Details

• Full-time position
• Hybrid — Bay Area, California
• Expected commitment of 40 hours per week
• Initial engagement of approximately 6 months
• Compensation: $55–$95/hour
• Candidates must live in the Bay Area and be available to work on-site with the assigned team multiple days per week when required
• Candidates not currently based in the Bay Area must be willing to relocate there at their own expense before the engagement begins
• Relocation assistance is not provided
• Client-issued accounts and equipment may be provided for work within designated systems and workflows
• Projects may be extended, shortened, or concluded based on organisational needs and performance

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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