Rust Backend Architect

Gramian ConsultancyAI training

Workable locations: India. Australia. Japan. Singapore. Philippines. New ZealandContractSenior

Salary not disclosed

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Job Details

Demonstrate strong hands-on proficiency in Rust through substantial professional, research, or open-source software development.
Have a strong understanding of backend service design, APIs, data persistence, and production software architecture.
Have practical knowledge of asynchronous programming, concurrency, error handling, and performance optimization in Rust.
Have experience analyzing and resolving complex backend correctness, scalability, reliability, or performance problems.
Be able to translate technical requirements into working implementations, reproducible tests, and verifiable outcomes.
Have experience with Rust workspaces, dependency management, test environments, and backend development tooling.
Demonstrate strong debugging, analytical reasoning, and technical problem-solving skills.
Have clear written communication and be able to explain architectural decisions and technical findings.
Be available to contribute approximately 15 hours per week and meet the project's minimum weekly task requirements.
Be able to begin work within 24–48 hours after completing onboarding.
Have strong written and verbal English.

Solve and validate Rust backend engineering problems involving APIs, service behavior, data persistence, concurrency, performance, and reliability.
Translate functional requirements, performance targets, and failure-handling expectations into reproducible implementation and testing workflows.
Design, review, and assess backend architectures for correctness, scalability, maintainability, and production readiness.
Prepare Rust crate workspaces, configuration files, test fixtures, dependency services, databases, and containerized development environments.
Develop and validate test cases covering expected behavior, edge cases, failure scenarios, and system reliability.
Debug complex backend issues and identify weaknesses in implementation, architecture, or system design.
Evaluate asynchronous and concurrent systems, including potential race conditions, resource contention, and performance bottlenecks.
Produce technical explanations and implementation artifacts that meet project specifications and support AI training and evaluation.
Maintain output quality while meeting weekly submission requirements and project deadlines.

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