[All remote jobs](https://jobicy.com/jobs.md)[![Binance logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/bc822f38-221.jpg)](https://jobicy.com/company/binance.md)[Binance](https://jobicy.com/company/binance.md) # AI Agent Engineer Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/binance.md)ShareRemote from[Singapore](https://jobicy.com/job-region/singapore.md), [Hong Kong](https://jobicy.com/job-region/hong-kong.md)SalaryUndisclosedDepartment[Software Engineering](https://jobicy.com/categories/engineering.md)EmploymentFull TimeExperienceOpen levelPublished24 Oct 2026Apply before23 Nov 2026Listing views36Application actions3Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. Binance is seeking an AI Agent Engineer to build enterprise-grade conversational agent capabilities for search, token intelligence, trading assistance, and strategy generation. The role combines backend engineering with LLM application development, including RAG, prompt engineering, function calling, memory, and workflow orchestration. The engineer will productionize reliable, observable, high-concurrency AI systems and improve quality through evaluation, monitoring, logs, and metrics. Close collaboration with product, data, algorithm, and trading teams is required to deliver customer-facing AI features. Familiarity with digital-asset markets and trader behavior is strongly valued. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 4/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThis is a technically demanding production AI role requiring strong backend system design alongside practical expertise in LLM agent architectures and reliability engineering. The trading domain, high-concurrency requirements, and fast-moving environment increase the complexity. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Market rate$160,000US market range (per year)$140k–$190k0$209.00k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer salary range is disclosed. The annual figures are AI estimates for a mid-level AI/LLM backend engineer in the US market and are not verified employer compensation; yearly cadence is inferred from standard full-time professional-role conventions. ## Core skills Skills and capabilities most closely associated with this opportunity. [Python](https://jobicy.com/jobs?search_keywords=Python.md)[Java](https://jobicy.com/jobs?search_keywords=Java.md)[Large Language Models](https://jobicy.com/jobs?search_keywords=Large%20Language%20Models.md)[AI Agents](https://jobicy.com/jobs?search_keywords=AI%20Agents.md)[Prompt Engineering](https://jobicy.com/jobs?search_keywords=Prompt%20Engineering.md)[Retrieval-Augmented Generation](https://jobicy.com/jobs?search_keywords=Retrieval-Augmented%20Generation.md)[Vector Databases](https://jobicy.com/jobs?search_keywords=Vector%20Databases.md)[Function Calling](https://jobicy.com/jobs?search_keywords=Function%20Calling.md)[Microservices](https://jobicy.com/jobs?search_keywords=Microservices.md)[System Design](https://jobicy.com/jobs?search_keywords=System%20Design.md)[Redis](https://jobicy.com/jobs?search_keywords=Redis.md)[Kafka](https://jobicy.com/jobs?search_keywords=Kafka.md)[Elasticsearch](https://jobicy.com/jobs?search_keywords=Elasticsearch.md)[Observability](https://jobicy.com/jobs?search_keywords=Observability.md)[Data Analysis](https://jobicy.com/jobs?search_keywords=Data%20Analysis.md) Sample interview questionsHow would you design a production conversational agent that can answer trading-related questions using internal and external tools?I would separate the system into an orchestration layer, a retrieval layer, governed tool interfaces, session-memory services, and an evaluation and observability pipeline. The orchestrator would classify intent, retrieve grounded context, select validated tools, enforce permissions and schemas, and provide safe fallback or clarification flows when confidence is low. What techniques would you use to reduce hallucinations in an LLM-based trading assistant? I would ground responses in versioned retrieval sources and trusted tool outputs, require citations or structured evidence where appropriate, constrain tool calling with schemas, and use confidence thresholds for clarification or refusal. I would also continuously evaluate factuality with curated datasets, production feedback, and adversarial test cases. How would you evaluate the quality of a multi-turn AI agent in production? I would combine offline evaluation sets with online metrics such as task completion, first-resolution rate, latency, fallback frequency, user satisfaction, and tool-error rates. I would segment results by intent and user journey, review sampled conversations, and use controlled A/B tests to validate improvements before broad rollout. Describe how you would make an agent platform resilient under high concurrency. I would use stateless scalable services, caching for repeated retrieval and metadata, asynchronous queues for noncritical workloads, rate limits, circuit breakers, and graceful fallbacks for model or tool failures. Distributed tracing, structured logs, SLOs, and capacity testing would provide the operational visibility needed to maintain availability and control latency. How would you work with product and trading stakeholders when defining an AI-powered token-insight feature? I would first translate user and business needs into specific supported intents, data sources, risk boundaries, and measurable success criteria. I would prototype critical flows with stakeholders, validate domain accuracy with trading experts, define evaluation cases from real questions, and iterate using production metrics and user feedback. Opportunity details ## About this role. Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, and more. Our mission is to increase the freedom of money and financial access for people around the world. Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by over 250 million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world. We are building AI Agent systems for core use cases such as AI conversations and AI-powered trading. We are looking for an AI Agent R&D Engineer to develop a conversational agent platform and its underlying capabilities, including tool calling, memory, orchestration, and more. The goal is to transform large language model capabilities into stable, reliable, and continuously evolving product features that can be applied to real business scenarios.. Why Binance • Shape the future with the world’s leading blockchain ecosystem • Collaborate with world-class talent in a user-centric global organization with a flat structure • Tackle unique, fast-paced projects with autonomy in an innovative environment • Thrive in a results-driven workplace with opportunities for career growth and continuous learning • Competitive salary and company benefits • Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team) Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success. By submitting a job application, you confirm that you have read and agree to our Candidate Privacy Notice. Responsibilities * Develop an enterprise-grade conversational agent platform to support core business scenarios such as AI search, token insight conversations, trading assistant Q&A, and trading strategy generation. * Design and implement multi-turn conversation capabilities, including contextual memory, tool calling and orchestration, clarification and follow-up questioning, and fallback handling, to create a natural and coherent conversational experience. * Build and optimize the large-model application pipeline, including prompt engineering, retrieval-augmented generation (RAG), tool calling / function calling, and workflow orchestration. * Work closely with product, algorithm, data, and trading teams to deploy conversational AI capabilities into real business scenarios and continuously drive iterative improvements. * Establish quality monitoring and evaluation systems for production environments, continuously improving key metrics such as first-resolution rate, conversation completion rate, response latency, and user satisfaction. * Ensure system stability, security, and compliance, while continuously improving performance, availability, and observability under high-concurrency scenarios. Qualifications * Master’s degree or above in Computer Science or a related field is preferred. * More than 2 years of backend development experience, with solid engineering skills in Java or Python and familiarity with common microservices architectures. * Hands-on experience in deploying large-model / AI applications, with a deep understanding of key technologies such as prompt engineering, RAG, vector retrieval, and function calling. * Strong complex system design capabilities, with familiarity in caching, message queues, databases, and service governance. * Strong interest in digital asset trading, market structure, on-chain data, and token-related information, with a willingness to deeply understand trader needs and behaviors. * Strong data analysis and troubleshooting skills, with the ability to drive continuous system improvement based on logs and metrics. * Strong cross-functional communication and project execution skills, with a results-oriented mindset. * Preferred Qualifications Experience in AI search, financial information retrieval, or token / project research products. Experience with trading products, market analysis, quantitative tools, or strategy platforms. Experience building agent platforms, A/B testing frameworks, or evaluation datasets. Familiarity with technologies such as Redis, Kafka, Elasticsearch, and vector databases. Why Binance * Shape the future of finance * Collaborate with world-class talent in a user-centric global organization with a flat structure * Tackle challenging projects in a fast-paced and innovative enviornment with autonomy * Thrive in a results-driven workplace with opportunities for career growth and continuous learning * Competitive salary and company benefits * Remote-first, work-from-home arrangement (may vary depending on the nature of the role and team) Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success. By submitting a job application, you acknowledge that you have read our [Candidate Privacy Notice](https://www.binance.com/en/candidate/privacy/notice). We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Show more [Apply now >](https://jobicy.com/jobs/156835-ai-agent-engineer.md) > Annual salary information is not provided for this position. 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