Data AI Engineer
Fireblocks is an enterprise-grade platform delivering a secure infrastructure for moving, storing, and issuing digital assets. It enables exchanges, custodians, banks, trading desks, and hedge funds to securely scale digital asset operations through its patent-pending SGX & MPC technology.
About Fireblocks
Fireblocks is an enterprise-grade platform that provides a secure infrastructure for moving, storing, and issuing digital assets. It enables financial institutions like exchanges, custodians, banks, trading desks, and hedge funds to securely scale their digital asset operations. The company was founded by Michael Shaulov, Idan Ofrat, and Pavel Berengoltz after they investigated a major cyber breach. Fireblocks utilizes breakthrough Multi-Party Computation (MPC) and patent-pending chip isolation technology to secure private keys and API credentials. The platform supports various use cases including treasury management, wallet as a service, tokenization, payments, and DeFi, and provides a complete development platform with APIs, SDKs, and tutorials for building on the blockchain.
Skills
About the Role
You will design and build LLM-powered systems that directly enhance product capabilities and customer experience, empowering Product, Engineering, and Business teams to make faster, data-driven decisions at scale. You will evaluate and quantify the business impact of AI initiatives through rigorous experimentation, benchmarking, and model evaluation to continuously optimize LLM performance. You will monitor, refine, and evolve AI models and solutions, iterating on prompt engineering and deployment practices to keep pace with advancing capabilities and business needs. You will use AI-assisted development tools like Cursor and Claude Code to accelerate delivery speed and engineering velocity. You will analyze large-scale datasets to surface strategic insights, define and track critical KPIs, and translate analytical findings into actionable recommendations.
Requirements
- Strong analytical background with experience defining KPIs and communicating data-driven recommendations
- 5+ years of experience in AI/ML engineering or a combined data analytics and AI role
- Hands-on experience with LLMs, prompt engineering, fine-tuning, and model evaluation pipelines
- Proficiency in Python and SQL; experience building and deploying production-grade AI applications
- Practical knowledge of MCP, database agents, and semantic views/YAMLs - Snowflake as a database agent platform - advantage
- Strong cross-functional communication skills
- Self-motivated and collaborative, able to operate independently within a global team
- Familiarity with the digital assets, fintech, or Web3 domain - advantage
Responsibilities
- Design and build LLM-powered systems that improve product capabilities and customer experience
- Evaluate and quantify the business impact of AI initiatives through experimentation, benchmarking, and model evaluation
- Monitor, refine, and evolve AI models and solutions by iterating on prompt engineering and deployment practices
- Leverage AI-assisted development tools to accelerate delivery speed and engineering velocity
- Analyze large-scale datasets to define and track KPIs and translate findings into recommendations