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Join Fireblocks as a Data Analytics AI Engineer to design LLM-powered systems, analyze large datasets, and drive data-driven decision making in a fast-paced environment.
About the Company
Fireblocks is a platform and network providing the simplest and most secure way for companies to work with digital assets. Trusted by major financial institutions, banks, globally-recognized brands, and Web3 companies including BNY Mellon, BNP Paribas, ANZ Bank, Revolut, and thousands more.
About the Team
Join the global Data team, which partners closely with Product, Engineering, and GTM stakeholders to power data-driven decision-making and AI-driven products across Fireblocks. The team has evolved from providing deep analysis to becoming enablers, bringing the right data and AI tools so that Sales, Marketing, and Customer Operations can run analysis and forecasting. Operating in a fast-paced, high-growth environment where much of what is built is new.
What You'll Do
- Design and build LLM-powered systems and data agents that directly improve internal capabilities, enabling GTM, Product, and Engineering teams to make faster, smarter, data-driven decisions at scale
- Analyze large-scale datasets to surface strategic insights across the customer lifecycle and revenue funnel; define and track critical KPIs; translate findings into actionable product and business recommendations
- Evaluate and quantify the business impact of AI initiatives through rigorous experimentation, benchmarking, and model evaluation to continuously optimize LLM performance
- Continuously monitor, refine, and evolve AI models and solutions, iterating on prompt engineering and deployment practices to keep pace with rapidly advancing capabilities
- Ship and maintain production-grade analytics and AI applications through modern CI/CD pipelines (GitLab/GitHub), ensuring reliable, repeatable, and observable deployments
- Manage and influence senior business stakeholders (including CRO-level), owning projects end-to-end and translating complex data and AI concepts into business outcomes
- Leverage AI-assisted development tools (e.g., Cursor, Claude Code) to accelerate delivery speed across the team
Requirements
- 5+ years of experience in AI/ML engineering or a combined data analytics and AI role
- Strong SQL proficiency; solid Python experience is a strong plus
- Hands-on experience with LLMs, prompt engineering, fine-tuning, and model evaluation pipelines
- Strong analytical background: experience defining KPIs and communicating data-driven recommendations to senior business stakeholders, with commercial acumen across Sales, Marketing, and revenue/pipeline
- Experience with CI/CD pipelines using GitLab or GitHub for analytics or AI workloads
- Demonstrated ability to own projects independently: scoping problems, navigating ambiguity, and managing stakeholder relationships without heavy oversight
- Strong cross-functional communication skills: able to present AI concepts and outcomes to both technical and non-technical audiences, up to CRO level
- Ability to work in NYC office approximately 3 days per week
Nice to Have
- Practical knowledge of Snowflake as a database agent platform, including MCP, database agents, and semantic views/YAMLs
- Experience with dbt (dbt Cloud preferred) for analytics engineering workflows
- Familiarity with the digital assets, fintech, or Web3 domain
What Success Looks Like
Within your first year, you will have delivered AI solutions and data agents with clear business impact across GTM and Product, become a trusted partner for data-driven AI initiatives across the organization, and helped elevate the team's velocity and capabilities.
Benefits
- Competitive base salary
- Target bonus
- Competitive equity grant
- Generous benefits
Employment Details
- Location: New York, US
- Employment type: Full-time
- Remote: Yes
- Salary: $156,000 - $204,000 USD per year
What We Offer
- Competitive salary range of $156,000 - $204,000.
- Total compensation package may include a target bonus and equity grant.
- Generous benefits and a diverse, inclusive work environment.