AI Enablement Engineer: BitGo

BitGo, a leading infrastructure provider for digital assets, is building an AI Enablement team to explore and deliver high-leverage AI automation for its internal engineering, support, and operations teams. As an AI Enablement Engineer, you'll be a key player in this effort, tasked with identifying inefficiencies and deploying practical AI copilots, integrations, and workflows that boost speed and quality. This is a hands-on role for an experienced backend engineer who is familiar with modern AI/ML systems and can take complete ownership of complex projects from start to finish.

Key Responsibilities
Partnership & Prototyping: Partner with internal teams to identify workflows that can benefit from applied AI, then quickly prototype durable solutions that are grounded in real-world constraints.

Design & Deployment: Design, deploy, and maintain internal AI systems that improve speed, accuracy, and clarity across teams.

AI Tool Lifecycle: Own the full lifecycle of internal AI tools—from initial exploration and rollout to long-term iteration. This includes prioritizing safety, observability, and maintainability.

Best Practices: Establish and evolve best practices for AI safety, context engineering, retrieval-augmented generation (RAG), and integration with existing systems.

Strategy: Help shape the company's internal strategy for AI adoption, creating frameworks for evaluating and scaling successful solutions.

Required & Preferred Qualifications
Required:

Experience: 5+ years of backend engineering experience, coupled with a strong product and systems mindset.

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

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

Soft Skills: Strong communication skills and the ability to reason rigorously about trade-offs and system constraints.

Preferred:

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

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

Familiarity with knowledge management systems (e.g., Confluence, Google Drive, Q&A bots).

An interest in the long-term strategy of AI adoption and change management.