Data Scientist, AI Agent Engineering
17 hours ago
About the Role We are building the next frontier of intelligent trading systems, leveraging AI Agents to autonomously handle complex workflows in fraud detection, customer support, risk monitoring, and operational decision-making. As a Data Scientist in AI Agent Engineering, you will design, build, and deploy production-grade multi-agent systems that reason, plan, and execute tasks at scale. You will work across agent orchestration, retrieval systems, safety guardrails, and MLOps to bring intelligent autonomy into our trading ecosystem. Responsibilities
- AI Agent Development & Orchestration: Design and implement multi-agent systems to manage fraud detection, risk monitoring, and operational workflows. Build middleware, task delegation, and communication protocols for seamless agent interaction.
- RAG & Knowledge Systems: Develop retrieval-augmented generation (RAG) pipelines integrating real-time market, regulatory, and trading data. Build and maintain vector databases and semantic search systems that power contextual agent decision-making.
- Safety & Governance: Implement safety frameworks, guardrails, and human-in-the-loop approval systems. Monitor agent behaviour, detect anomalies, and enforce regulatory and business compliance.
- Agent CI/CD & Infrastructure: Develop agent testing, versioning, and deployment pipelines. Build A/B testing frameworks, rollback strategies, and monitoring systems to optimise production agents.
- Collaboration: Work closely with risk, infrastructure, and product teams to embed safety constraints, streamline agent-human interaction patterns, and adapt agent solutions to business needs.
- 2+ years of experience in machine learning or AI systems development.
- Strong background in LLMs, prompt engineering, and AI Agent frameworks (LangChain, LlamaIndex, CrewAI, AutoGen, etc.).
- Hands-on experience with RAG systems, vector databases, and real-time data integration.
- Proficiency in Python; familiarity with FastAPI, Celery, or Ray a plus.
- Experience with APIs (OpenAI, Anthropic) and LLM fine-tuning.
- Knowledge of big data tools (Spark, Kafka, Redis) and containerized environments (Docker, Kubernetes).
- AI Agent Specialization: Workflow design (planning, reasoning, tool use), guardrails and oversight frameworks, semantic search, monitoring, and rollback strategies.
- Background: Master's degree (or equivalent experience) in Data Science, AI Engineering, or Applied ML. Experience with large-scale, real-time systems; financial or trading domain knowledge preferred.
- Soft Skills: Strong problem-solving and communication skills, ability to work in fast-changing 0→1 environments, and a passion for AI agents, LLMs, and intelligent automation.
• 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. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. 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.
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