Trading Analytics Developer, Quantitative Trading

The Quant Trading team manages risks associated with various crypto products, including spots and derivatives. They develop and implement trading strategies in fast-paced and complex trading environments.

We are looking for a Trading Analytics Developer to join our Quant Trading team. This role entails advancing our data and AI infrastructure by merging traditional quantitative development with cutting-edge AI platform engineering. The focus is on constructing robust, scalable systems catering to data analytics and artificial intelligence workloads. The ideal candidate will ensure reliability, performance, and actionable insights across high-performance trading systems and modern AI capabilities.

Primary Responsibilities

Data Platform & Analytics

• Design, construct, and oversee high throughput batch and streaming data pipelines utilizing technologies like Kafka, Flink, and ETL
• Create and fine-tune analytical data models for time-series, financial metrics, and trading activity
• Manage analytical databases such as ClickHouse, MongoDB, BigQuery, Snowflake, or alike, with a cost-efficient architecture
• Develop resilient data pipelines with strong backfill and reconciliation features
• Establish comprehensive monitoring for data quality, freshness, and pipeline dependability

AI Platform Development

• Design, build, and manage internal AI platforms for multiple trading teams
• Develop vector search systems employing optimized HNSW indexing and hybrid retrieval capabilities
• Implement evaluation frameworks for retrieval quality and RAG systems
• Build reusable AI tools, including standardized RAG pipelines, prompt management, and self-service workflows
• Create and maintain agent systems utilizing modern frameworks like LangGraph, A2A, MCP, focusing on controllability and auditability

Technical Requirements

Mandatory Foundations

• 5+ years of production experience in Python and Java in high-performance settings
• Sound software engineering fundamentals encompassing system design, data structures, algorithms, data integrity, accuracy, and performance optimization
• Expertise in Linux, Github, and modern CI/CD practices
• Demonstrated experience with AWS cloud services and Kubernetes orchestration
• Proficiency in handling large-scale, complex datasets in financial/trading contexts

Data Platform Expertise

• Proficiency in advanced SQL with window functions, query optimization, and real-time data synchronization, alongside expertise in database design and infrastructure support
• Experience with data workflow and messaging orchestration tools like Airflow, Jenkins, AMPS, etc.
• Expertise in metric design and implementation for trading analytics, time-series data visualization with Grafana, TradingView, and BI tools, and working with Kafka, Flink, and event processing in production environments

AI Platform Capabilities

• Design and optimize vector search systems with considerations for recall, latency, and memory trade-offs
• Proficiency in retrieval system evaluation methodologies, RAG pipeline architecture, LLMOps practices, and AI agent framework experience in production settings like A2A and MCP

Preferred Qualifications

Financial/Trading Domain

• Experience in trading systems, quantitative finance, or financial technology
• Understanding of market data and data subscription using Rest API/Web Socket
• Knowledge of cryptocurrency markets, DeFi, and related technologies

Professional Attributes

• Excellent problem-solving skills with the ability to perform under pressure
• Strong communication skills for cross-team collaboration
• Proactive approach to system reliability and performance optimization
• Continuous learning mindset in the rapidly evolving AI/ML landscape
• Balancing practical engineering rigor with innovative solution development

Life at Crypto.com

• Opportunities for growth, a proactive working environment, and facilitation of personal and professional development
• Collaborative work culture with a focus on supporting each other and stakeholders to achieve common goals
• Embracing diversity, equal opportunities, and fostering transparency and fairness
• Personal data provided by applicants will be used for recruitment purposes only.
• Recruitment processes may involve the use of artificial intelligence tools to analyze candidate qualifications before human evaluation.
• Personal data processing details can be provided upon request.