AI enablement engineer

Responsibilities: AI Adoption & Stakeholder Enablement • Partner with Department Heads and business stakeholders to identify workflow pain points, assess AI applicability, and design and deliver tailored AI solutions using Google Gemini and Claude Enterprise. • Build and maintain a library of reusable AI skills, prompt templates, and custom instructions for common business functions across departments such as finance, compliance, operations, and customer support. • Plan, deliver, and iterate on AI training sessions, workshops, and onboarding materials for both business and technical audiences; track adoption metrics and report progress to management. Developer Enablement • Embed with engineering teams to coach developers on effective AI-assisted development practices, including advanced Claude Code usage, prompt patterns, and MCP server integrations that improve engineering productivity. • Design, build, and maintain AI agents and automated workflows that integrate enterprise AI capabilities with internal systems via REST APIs and MCP servers. Security, Governance & Compliance • Ensure all AI solutions and integrations are designed and deployed in alignment with BTSE’s information security policies, data handling standards, and regulatory obligations; work closely with the Information Security team to review AI use cases for data classification and acceptable use compliance. • Maintain documentation of approved AI tools, integration patterns, and usage guidelines; contribute to AI governance artefacts such as acceptable use policies, risk assessments, and audit trail requirements. Programme Management & Reporting • Own the AI enablement programme roadmap: prioritise initiatives across departments, manage concurrent workstreams, communicate status to leadership, and measure outcomes against defined adoption and productivity KPIs. • Stay current with the rapidly evolving AI tool landscape; evaluate new capabilities across our enterprise platforms, run proof-of-concept pilots, and make evidence-based recommendations on expansion or new tooling. Requirements: • 3+ years of experience in a technical role such as solutions engineer, developer advocate, technical consultant, or software engineer, with a strong focus on AI/ML tooling or enterprise enablement. • Hands-on experience with Claude Enterprise (claude.ai) and/or the Anthropic API, including working with system prompts, tool use, and multi-turn conversations. • Practical knowledge of Google Gemini for Workspace (Docs, Sheets, Gmail, Meet) and the ability to guide end users in applying it effectively to business tasks. • Ability to design and build reusable AI skills, custom instructions, and prompt templates tailored to specific business functions (e.g. finance reporting, compliance summaries, customer support drafting). • Demonstrated ability to engage with non-technical stakeholders, conduct workflow discovery sessions with Department Heads, and translate business requirements into AI-powered solutions. • Ability to work alongside software engineers, providing guidance on effective use of AI-assisted development tools such as Claude Code, and recommending prompt patterns or agentic workflows that improve engineering productivity. • Programming proficiency in at least one language (Python, Java, Go, or JavaScript) sufficient to build proof-of-concept integrations, automation scripts, and AI agent workflows. • Familiarity with REST APIs and the ability to integrate AI capabilities into existing internal tooling or workflows via API calls. • Experience facilitating training sessions, workshops, or knowledge-sharing sessions on AI tools and best practices for mixed-audience groups (business users and technical staff). • Strong written and verbal communication skills; able to document AI solutions clearly for both end-user guides and technical handover. • Able to effectively listen, speak, read and write in English, with Chinese as a plus. Nice to haves: • Familiarity with Model Context Protocol (MCP) — either consuming existing MCP servers or building custom ones to extend AI tool access to internal systems. • Exposure to vector databases, embeddings, or RAG pipelines (e.g. pgvector, Chroma, or similar) for grounding AI outputs in company-specific knowledge. • Knowledge of information security principles and data handling requirements in a regulated industry (fintech, crypto, or financial services); understanding of how to apply AI tools within a data governance framework. • Background in change management or organisational adoption programmes; experience measuring and reporting on software or AI adoption KPIs. • Familiarity with the fintech or cryptocurrency domain — understanding of common workflows across operations, compliance, customer support, and engineering teams. • Prior experience authoring internal knowledge bases, wikis (e.g. Confluence), or developer-facing documentation for AI tools and processes. Perks and Benefits • Competitive total compensation package • Various team building programs and company events • Comprehensive healthcare schemes for employees and dependants • And many more! Apply and let us tell you more!