AI Enablement Engineer at BitGo

BitGo is a leading infrastructure provider of digital asset solutions, offering services like custody, wallets, staking, trading, financing, and settlement from regulated cold storage. Founded in 2013, BitGo serves thousands of institutions and millions of retail investors worldwide, acting as the operational backbone for a significant portion of Bitcoin network transactions.

About the Role:
The AI Enablement team explores and delivers high-leverage AI automation for internal engineering, support, and operations teams. This role involves partnering with internal users to identify areas for improvement, then building and deploying practical copilots, integrations, and workflows. The goal is to unlock new ceilings on speed and quality across the company.

Responsibilities:

Partner with stakeholders across the company to identify workflows that can benefit from applied AI and prototype durable solutions.

Design, deploy, and maintain internal AI systems that improve speed, accuracy, and clarity.

Track the effectiveness of deployed AI systems through user feedback and metrics.

Own the full lifecycle of internal AI tools, prioritizing safety, observability, and long-term maintainability.

Establish and evolve best practices for AI safety, context engineering, and retrieval-augmented generation (RAG).

Help shape BitGo's internal strategy for AI adoption.

Requirements:

Required Qualifications:

Experience building human-in-the-loop systems, LLM-powered agents, or AI copilots in a production environment.

Familiarity with the practical application of AI/ML techniques, including context engineering, embeddings, vector stores, and LLM APIs.

Ability to reason rigorously about trade-offs, system constraints, and long-term maintainability.

Strong communication and stakeholder engagement skills.

5+ years of backend engineering experience with a strong product and systems mindset.

Preferred Qualifications:

Experience in observability, operational excellence, or developer experience roles.

Experience delivering internal-facing tools or automation that improved developer/operator workflows.

Familiarity with knowledge management systems (e.g., Confluence, Google Drive).

Interest in AI adoption strategy, internal evangelism, and change management.