AI Enablement Engineer

Who We Are:
Galaxy is a global leader in digital assets and data center infrastructure, delivering solutions that accelerate progress in finance and artificial intelligence. We believe that blockchain and digital asset innovation will transform how value moves through the world – and we’re building the products and services to make that future a reality.

Our institutional digital assets platform spans trading, investment banking, asset management, staking, self-custody, and tokenization technology. We also invest in and operate cutting-edge data center infrastructure to power AI and high-performance computing, addressing the growing demand for scalable energy and compute in the U.S.

We work at the intersection of finance and technology, helping institutions, startups, and developers navigate a digitally native economy. Led by CEO and Founder Michael Novogratz, our team blends deep crypto expertise with institutional experience and a shared commitment to shaping the future of Web3 and AI.

Galaxy is headquartered in New York City, with offices across North America, Europe, the Middle East, and Asia.

To learn more about our businesses and products, visit www.galaxy.com.

What We Value:

We are a diverse team of free thinkers, and fast movers united to help investors and creators energize the global economy. We are looking for individuals who thrive in a culture of builders and overachievers and embrace high performance, transparent feedback, and a mission-first approach. Our culture shapes our way of working and gets us where we want to be.

• Seek Excellence.

• Be Selective To Be Effective.

• Be Highly Aligned, Loosely Coupled.

• Disagree Transparently.

• Encourage Independent Decision-Making.

• Build Dream Teams.

Team Overview

The Applied AI (AI Enablement) team is a newly formed, strategic function focused on accelerating enterprise-wide adoption of generative AI technologies. We build the foundational infrastructure, tools, and expertise that enable teams across the organization to leverage AI effectively and responsibly.

Role Summary

We're seeking an AI Enablement Engineer to join our team in building, deploying, and scaling AI solutions across the enterprise. You'll work at the intersection of machine learning engineering, data engineering, and platform operations—building RAG systems, evaluating cutting-edge LLM models, and serving as a trusted advisor to business units and corporate functions navigating their AI adoption journey.

Key Responsibilities

AI Infrastructure & Model Development

• Design, build, and optimize Retrieval-Augmented Generation (RAG) systems for various enterprise use cases

• Develop and maintain data ingestion pipelines (Python and other scripting languages) to populate and manage vector databases

• Deploy and maintain AI infrastructure including Amazon Bedrock and Ollama environments

• Implement evaluation frameworks and tooling (such as LLMComparator) to systematically compare LLM performance across different models and use cases

Model Evaluation & Selection

• Conduct rigorous evaluations of LLM models for diverse applications including RAG, coding agents, and domain-specific tasks

• Establish benchmarking standards and best practices for model selection

• Stay current with the rapidly evolving LLM landscape and provide recommendations on emerging capabilities

Enterprise AI Enablement & Consulting

• Partner with teams, business units, and corporate functions to assess their AI needs and design appropriate solutions

• Provide guidance on build vs. buy decisions—advising when third-party GenAI tools are appropriate versus when internal capabilities should be leveraged

• Enable teams in adopting AI-assisted development tools including Claude Code, Cursor, and GitHub Copilot

• Develop documentation, training materials, and best practices for enterprise AI adoption

Platform Operations

• Ensure reliability, performance, and cost-effectiveness of AI infrastructure and services

• Monitor and optimize vector database performance and model inference costs

• Collaborate with security and compliance teams to ensure responsible AI deployment

Required Qualifications

• 6+ years of experience in any of the following: Site reliability engineering (SRE), Software engineering, Data engineering (DBA/DBRE), or Machine learning engineering

• Strong proficiency in Python and experience building data pipelines

• Hands-on experience with LLMs and understanding of prompting techniques, fine-tuning, and RAG architectures

• Experience with vector databases (e.g., Pinecone, Weaviate, pgvector, ChromaDB)

• Familiarity with cloud platforms, particularly AWS services

• Excellent communication skills with ability to explain technical concepts to non-technical stakeholders

• Demonstrated ability to work independently and drive projects from concept to production

Preferred Qualifications

• Experience with Amazon Bedrock, SageMaker, or similar managed ML services

• Familiarity with Ollama or other local LLM deployment frameworks

• Background in evaluating and benchmarking ML models

• Experience with AI-assisted coding tools (Claude Code, Cursor, GitHub Copilot, etc.)

• Understanding of MLOps practices and tools

• Previous consulting or internal enablement experience

• Knowledge of responsible AI practices and governance frameworks

What You'll Bring

• Technical versatility: Comfort moving between infrastructure work, model evaluation, and application development

• Consultative mindset: Ability to understand business problems and translate them into technical solutions

• Rapid learning: The AI landscape evolves quickly—you stay curious and adapt

• Pragmatism: You balance innovation with practical delivery and know when "good enough" is the right answer

• Collaboration: You enjoy partnering with diverse teams and building relationships across the organization

What We Offer

• Opportunity to shape AI strategy and adoption at the enterprise level

• Work with cutting-edge AI technologies and tools

• High-visibility role with exposure to leadership and diverse business units

The base salary ranges included below will be commensurate with candidate experience, expertise and local market. Final offer amounts are determined by multiple factors, including candidate experience and expertise. At Galaxy, we maintain a total compensation philosophy which consists of a competitive base salary, annual bonus, and equity incentives.

Base Salary Range
$175,000—$220,000 USD

Galaxy respects diversity and seeks to provide equal employment opportunities to all employees and job applicants for employment without regard to actual or perceived age, race, color, creed, religion, sex or gender (including pregnancy, childbirth, lactation and related medical conditions), gender identity or gender expression (including transgender status), sexual orientation, marital or partnership or caregiver status, ancestry, national origin, citizenship status, disability, military or veteran status, protected medical condition as defined by applicable state or local law, genetic information or predisposing genetic characteristic, or other characteristic protected by applicable federal, state, or local laws and ordinances.

We will endeavor to make a reasonable accommodation to the known limitations of a qualified applicant with a disability unless the accommodation would impose an undue hardship on the operation of our business. If you believe you require such assistance to complete the application process or to participate in an interview, please contact [email protected].