Backend Developer Jobs (No ghost jobs, direct from employers)

Responsibilities

• Design and implement solutions for user incentives, experience improvements, and business automation in support of retention goals. Independently drive requirements analysis, technical design, development, testing, production rollout, ongoing operation, and post-launch evaluation for your modules.

• Develop and maintain user incentive and financial benefit modules. Strengthen rule execution, monetary calculations, disbursement, state transitions, idempotency, consistency, failure compensation, reconciliation, and auditing to ensure accuracy and traceability.

• Contribute to the engineering and productionization of AI applications and AI-powered user experiences, continuously improving output quality, responsiveness, system stability, and operating costs.

• Bring AI into real-world use cases by designing, developing, and iterating on AI Agents and agentic workflows. Integrate models, tools, and internal systems to support knowledge retrieval, troubleshooting, operational assistance, and business automation.

• Establish evaluation, execution observability, and safety controls for AI workflows. Improve context and state management, failure recovery, budget controls, and human intervention mechanisms. Enforce data access permissions, sensitive information protection, and boundaries on fund-related operations. Ensure that critical monetary calculations and writes are governed by deterministic rules and authorized execution paths.

• Help build team-wide AI-assisted engineering workflows. Develop reusable Skills, tools, context conventions, and validation mechanisms to enable effective AI use in requirements analysis, development, testing, code review, and troubleshooting, improving delivery efficiency while maintaining engineering quality.

Required Qualifications

• A bachelor's degree or above in Computer Science or a related field, with at least four years of backend development experience. Either Go or Java is acceptable.

• Strong programming fundamentals, including knowledge of the concurrency model, memory management, and performance optimization of at least one mainstream backend language. Ability to independently troubleshoot complex issues.

• Experience developing distributed systems and contributing to the design of core business modules or systems. Hands-on experience handling concurrency conflicts, idempotency, duplicate message consumption, cross-service consistency, timeouts, and failure recovery.

• Proficiency with common backend technologies, including RPC frameworks, caches, message queues, and relational databases, with an understanding of their appropriate use cases and reliability limitations.

• AI-assisted engineering capability - a core requirement: Proficiency in using AI coding tools for requirements decomposition, system analysis, coding, testing, and code review. Ability to validate outputs and maintain engineering quality rather than relying solely on generated code.

• AI application engineering capability - a core requirement: Hands-on experience developing and deploying AI/LLM capabilities in real-world scenarios. Ability to clearly explain the problem definition, personal contribution, technical trade-offs, and outcome validation. Experience must extend beyond basic tool usage or demonstration-only projects.

• Fund-related business experience - a mandatory requirement: Hands-on development experience with systems involving funds or monetary value, such as commission rebates, settlement, reconciliation, payments, accounting ledgers, vouchers, promotional credits, or subsidies. Experience addressing monetary precision, duplicate disbursements, failure compensation, or financial reconciliation, with the ability to explain the stages you owned and the mechanisms used to ensure correctness.

• Proactivity, business understanding, and cross-functional collaboration skills. Ability to translate business goals into technical problems and acceptance criteria. Commitment to testing, code review, observability, permission boundaries, and data security, with ownership of delivery and production outcomes.

Preferred Qualifications

• AI Agent / agentic workflow development experience - a key priority: Hands-on experience designing, developing, and continuously iterating on Agent workflows involving tool calling, workflow orchestration, context and memory management, state persistence, failure recovery, or human intervention. Projects may include business products, internal tools, or actively used and maintained personal projects.

• Experience evaluating Agent performance and improving reliability. Ability to identify issues through evaluation datasets, failure cases, execution traces, or business metrics, and validate the impact of improvements.

• Experience building team-wide AI-assisted engineering workflows, such as custom Skills, Rules, context conventions, automated testing, or AI code review pipelines that have been adopted by the team.

• Experience independently owning complex business modules or driving cross-system projects, including proposing solutions, coordinating dependencies, and delivering outcomes.

• Familiarity with complex rule systems, microservices, and asynchronous task orchestration. Ability to determine when to use traditional workflows versus Agents based on cost, determinism, and error risk.

Additional Advantages

• Experience developing retention, user incentive, lifecycle engagement, or growth platforms, including collaboration with Product and Operations to evaluate outcomes using business data and experiments.

• Practical experience with RAG, vector retrieval, knowledge bases, MCP, AI translation, search, or Agent orchestration frameworks, with the ability to explain technology choices and their limitations.

• Engineering experience at a cryptocurrency exchange or fintech company, or actively maintained and used personal projects and open-source contributions.