Backend Engineer – AI Pro, Agent Infrastructure

This is a fully remote position, open to applicants in Singapore.

📋 Description

• Develop and enhance key components of the Agent Runtime, which includes intent routing, query rewriting, RAG, tool/skill orchestration, and multi-step agent workflows.

• Design and optimize capabilities for Tool Server / Tool Calling, focusing on tool discovery, execution, result handling, and integration with web search, market data, and internal services.

• Create evaluation datasets and harnesses to assess routing accuracy, answer quality, tool-use performance, and agent reliability.

• Analyze and improve agent quality through failure analysis, regression detection, prompt/workflow optimization, and evaluating guardrail effectiveness.

• Enhance system observability and reliability by implementing tracing, metrics, logging, dashboards, and production monitoring.

• Troubleshoot issues across asynchronous services and agent pipelines.

• Create integration tests utilizing mocked LLM responses and replayable evaluation scenarios.

• Work collaboratively with Backend, Data Science, and Algorithm engineers to experiment, benchmark, and deploy AI capabilities into production.

• Transform concepts from prototype to benchmark and finally into production.

• Execute significant engineering projects from problem definition to implementation, evaluation, and production.

⛳️ Requirements

• Currently enrolled in university or a recent graduate.

• Proficient in Python programming with a solid foundation in software engineering principles.

• Strong knowledge of algorithms, data structures, and problem-solving techniques.

• Practical experience with LLM applications or agent systems acquired through research, coursework, internships, or projects.

• Familiarity with RAG, Tool Calling, Function Calling, Prompting, agent workflows, or LLM evaluation.

• Comfortable working with real codebases, APIs, asynchronous services, testing, CI/CD practices, and code review processes.

• Excellent debugging and analytical skills.

• Experience with agent frameworks such as LangGraph, LangChain, AgentScope, LlamaIndex, or similar (preferred).

• Familiarity with MCP, tool ecosystems, or Agent Runtime (preferred).

• Experience in building benchmark, evaluation, or LLM testing infrastructure (preferred).

• Knowledge of vector search, embeddings, RAG evaluation, or LLM observability (preferred).

• Experience with Redis, Kafka, Docker, Kubernetes, or cloud-native systems (preferred).

• Exposure to LLM security, guardrails, prompt-injection defense, or tool-use safety (preferred).

• Experience with model inference, latency optimization, or cost optimization (preferred).

🏝️ Benefits

• Competitive salary and comprehensive company benefits.

• Flexible work-from-home arrangement (subject to business team requirements).

• Opportunities for career advancement and continuous learning.

• Networking and professional development opportunities.

• Development of a professional network and transferable skills.

• Contribute to real features for a production AI Agent utilized by Binance users.

• Learn from experienced Backend, Data Science, and Algorithm engineers.

• Take ownership of significant engineering projects from start to finish.