Rust Backend Architect - AI Training Projects

JobgetherAI training

Work remotely from United StatesContractSenior

Salary not disclosed

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Job Details

Demonstrate strong hands-on proficiency in Rust through professional experience, research projects, or significant open-source contributions.
Have extensive understanding of backend service development, API design, data persistence, and production-grade software architecture.
Bring practical experience with asynchronous programming, concurrency models, error handling, and performance optimization in Rust.
Be able to diagnose and resolve complex backend challenges involving correctness, scalability, reliability, and performance.
Translate technical requirements into functional implementations and reproducible, verifiable test scenarios.
Be familiar with Rust workspaces, crate organization, dependency management, testing frameworks, and backend development tools.
Apply debugging skills and analytical reasoning to complex technical problems.
Understand software testing principles, edge-case analysis, failure handling, and validation of system behavior.
Assess architectural trade-offs and clearly communicate technical decisions related to reliability, maintainability, and performance.
Document implementation details and explain complex engineering findings in English.
Work autonomously with attention to detail and deliver technically accurate, well-documented work.
Be available to contribute approximately 15 hours per week and meet minimum weekly task requirements.
Be able to start within 24–48 hours after onboarding; immediate availability is preferred.

Implement and validate Rust backend solutions involving APIs, persistence, concurrency, performance, and reliability.
Translate functional specifications and failure-handling requirements into implementations and reproducible testing workflows.
Design, review, and evaluate backend architectures for correctness, scalability, maintainability, and production readiness.
Set up and maintain Rust workspaces, configuration, dependencies, test fixtures, databases, and containerized development environments.
Develop and execute tests for expected behavior, edge cases, errors, failure scenarios, and system reliability.
Debug complex backend issues and identify weaknesses in code, architecture, and system design.
Analyze asynchronous and concurrent systems for race conditions, resource contention, deadlocks, and performance bottlenecks.
Assess implementations against technical specifications and engineering standards.
Document implementation details and architectural decisions for AI training and evaluation activities.
Manage assigned tasks independently and meet weekly submission requirements and project deadlines.

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