Lead Software Engineer, Clearing Engineering

About Bullish

Bullish is an institutionally focused global digital asset platform that provides market infrastructure and information services. These include:  Bullish Exchange – a regulated and institutionally focused digital assets spot and derivatives exchange, integrating a high-performance central limit order book matching engine with automated market making to provide deep and predictable liquidity. Bullish Exchange is regulated in Germany, Hong Kong, and Gibraltar.  CoinDesk Indices – a collection of tradable proprietary and single-asset benchmarks and indices that track the performance of digital assets for global institutions in the digital assets and traditional finance industries.  CoinDesk Data - a broad suite of digital assets market data and analytics, providing real-time insights into prices, trends, and market dynamics.  CoinDesk Insights – a digital asset media and events provider and operator of [Coindesk.com]( a digital media platform that covers news and insights about digital assets, the underlying markets, policy, and blockchain technology.

Director, Engineering

At Bullish, we are engineering the institutional standard for the digital asset industry. Our mission is to build a platform centered on security and compliance, requiring a commitment to technical excellence that extends beyond simply delivering code. As a global organization, we set a high bar for those driven to do their best work alongside world-class peers.

We value engineers who treat development as a craft and own the outcome from concept to deployment. We expect our teams to bring structure to ambiguity and shape the frameworks that support our global organization. We refuse to compromise on quality and seek problem solvers who thrive on high-impact technical challenges.

The Clearing Engineering Team builds the mission-critical infrastructure for Bullish Clearing. We mitigate systemic risk through automated default management and ensure operational integrity via high-precision data validation. Our proprietary netting algorithms drive capital efficiency and market velocity, reducing liquidity requirements while accelerated settlement cycles provide participants with faster access to funds. We solve complex distributed systems challenges on a modern cloud-native stack, rejecting "good enough" in favor of the engineering rigor required to operate within highly regulated jurisdictions.

• Design, build, and maintain high-performance risk systems for the Clearing function.
• Architect scalable infrastructure to efficiently ingest and transform market data feeds.
• Apply a deep understanding of data models and workflows across Risk Management, Regulatory Reporting, and Clearing.
• Guarantee system resilience by prioritizing high availability, disaster recovery, data freshness, and throughput (TPS).
• Champion engineering excellence, enforcing high standards for code quality, automated testing, and SDLC best practices.
• Identify and resolve functional bottlenecks and cost inefficiencies through continuous performance profiling.
• Collaborate with global teams (HK, NY)—including Product Managers, Quants, and Risk Managers—to distill complex requirements into clear technical specifications.
• Drive the evolution of the platform’s target-state architecture, staying current with industry trends to ensure continuous improvement.

• 10+ years of engineering experience supporting front office trading systems at a regulated financial institution.
• Deep knowledge of risk management frameworks, including margining methodologies (Initial Margin, Variation Margin, SPAN, VaR), default waterfall mechanics, real-time Mark-to-Market (MtM) valuation, stress testing, and backtesting engines.
• Solid understanding of derivatives, including Options, Futures, and Greeks (Delta, Gamma), and their impact on risk profiles.
• Expert-level Java proficiency, with a track record of building fault-tolerant, high-throughput systems.
• Deep experience in performance tuning, garbage collection (GC) optimization, concurrency, and memory management.
• Implementation experience with middleware, specifically Aeron and Kafka.
• Expertise in designing clean data structures, event schemas, and database models.
• Proficiency managing both SQL and NoSQL data stores (e.g., Postgres, Redis, MongoDB).
• Deep understanding of testing methodologies and SDLC best practices, including Twelve-Factor App, distributed HA/DR strategies, and hexagonal architecture.
• Ability to use Large Language Models (e.g., Claude, Gemini) to accelerate development without sacrificing engineering standards.
• A strong sense of ownership and an outcome-oriented mindset.
• Agility to thrive in a dynamic startup environment.
• Commitment to a collaborative culture, evidenced by active mentorship and knowledge sharing.

• Proficiency with cloud and DevOps ecosystems (e.g., AWS, GCP, Kubernetes, Docker) and workflow orchestration (e.g., Airflow, DBT).
• Knowledge of FIX and FIXML protocols.
• Familiarity with big data management and data lake ecosystems (e.g., Databricks, Snowflake, BigQuery).
• Experience with BI tools for data visualization (e.g., Tableau, Superset).