• Support research and studies related to Artificial Intelligence • Test and explore AI tools applied to software development and software quality • Assist in creating prompts, automated workflows and small prototypes • Support initiatives to automate tasks using AI • Participate in documenting processes, tests and learnings • Collaborate with Software Quality, Automation and Development teams • Contribute ideas for continuous improvement of processes and products • Participate in project meetings, training sessions and activities.

• Define and own the AI roadmap, starting with go-to-market and expanding across the business, from use-case discovery and prioritisation through to delivery, adoption and measurement. • Identify where AI, automation and workflow redesign can remove friction, in go-to-market first and then the wider business. • Act as the connective tissue between business stakeholders and technical teams, translating operational challenges into concrete, prioritised delivery work. • Build a clear intake, prioritisation and delivery model for AI use cases, ensuring the team focuses on high-impact problems rather than isolated experiments. • Evaluate build vs. buy decisions across AI tooling, workflow automation, business systems and internal productivity tools. • Champion practical, responsible AI adoption across the company, ensuring what gets built is useful, trusted and embedded into how people work. • Partner with Legal, Security, IT, Data Warehouse and Analytics teams to ensure AI adoption is scalable, compliant and aligned with internal governance. • Help teams move from AI experimentation to repeatable workflows that improve productivity, quality, accuracy and decision-making. • Lead and develop your Engineering Manager, who owns day-to-day technical execution for the technical delivery team. • Set technical direction and priorities alongside the EM by challenging scoping, reviewing tradeoffs, and removing blockers. • Provide enough technical fluency to challenge assumptions, evaluate solutions, and ensure the right problems are being solved in the right way. • Work closely with Data Warehouse and Analytics teams to ensure AI workflows are grounded in reliable data and aligned with existing data architecture. • Foster a culture of experimentation, pragmatic delivery, continuous improvement and measurable business impact. • Ensure AI and automation initiatives are delivered with appropriate documentation, ownership, adoption plans and feedback loops. • Own Revenue Operations: the systems and data behind the revenue engine (CRM, pipeline, lead routing and forecasting). • Make RevOps one of the first proving grounds for AI: improve accuracy, speed and rep productivity, and build it. • Drive operational change that sticks, ensuring teams do not just receive new tools but adopt better ways of working. • Build trust with senior stakeholders by clearly communicating priorities, trade-offs, risks and expected outcomes. • Create practical enablement, guidance and feedback mechanisms to support AI adoption across different functions. • Measure adoption and impact, using feedback and business outcomes to refine the AI Operations roadmap. • Help the business distinguish between genuine AI opportunities and low-value experimentation or hype.

• AI Use Case Discovery and Prioritization • Partner with clinical, operational, finance, human resources, and technology teams to identify repetitive, manual, or high-friction workflows that may benefit from AI-enabled automation. • Evaluate potential use cases based on business value, feasibility, scalability, and user impact. • Translate business needs into practical automation concepts, prototypes, and deployable solutions. • Identify opportunities to reduce administrative burden and improve employee productivity through responsible use of AI. • Solution Design, Build, and Deployment • Design, build, test, and deploy AI-powered workflows, chatbots, assistants, agents, and automations using approved enterprise tools and platforms. • Create prompts, instructions, knowledge libraries, and workflow logic that enable AI solutions to provide accurate, reliable, and useful outputs. • Build employee-facing AI assistants that help users find information, answer questions, and complete routine tasks. • Configure chatbot knowledge sources using company documentation, policies, procedures, and other approved content. • Rapidly prototype solutions and iterate based on user feedback and business needs. • Continuously improve existing solutions to increase usability, adoption, and business value. • Measurement and Continuous Improvement • Define expected outcomes and success measures for solutions and pilots. • Track results such as time savings, productivity improvements, adoption rates, and process efficiency. • Document lessons learned and recommend opportunities for expansion or improvement. • Help establish repeatable methods for evaluating AI use cases across the organization. • Governance, Compliance, and Responsible Use • Ensure AI solutions align with HIPAA, privacy requirements, organizational security standards, and established governance practices. • Incorporate appropriate human review and oversight into workflows when needed. • Support documentation of solution design, data sources, and operational controls. • Promote responsible and secure use of AI technologies. • User Enablement and Adoption • Create simple user guides, reference materials, and training content. • Demonstrate solutions to end users and stakeholders. • Gather user feedback and incorporate improvements into future releases. • Support the adoption of AI-enabled ways of working across the organization. • Innovation and Practice Development • Stay current on emerging AI tools, platforms, and capabilities. • Recommend opportunities to pilot new technologies that may improve productivity or efficiency. • Contribute to the development of the AI Incubator's standards, practices, and operating model. • Help build a scalable AI automation practice from the ground up.

Role Description We're building a new AI Operations function, and this is the role that leads it, reporting to the Chief AI Officer. Your mandate is to drive AI adoption across the company, starting where the value is highest: our go-to-market functions, Sales, Marketing and Customer Success, then expanding across the rest of the business over time. Your core job is delivery, finding where AI can remove friction and leading a technical team to build and ship solutions, while partnering with Legal, Security, IT and Finance on the governance and economics around them. You'll embed directly with teams, ship working solutions in days rather than quarters, and turn one-off wins into reusable assets the whole company can build on. You are not walking into a blank slate. Every Leadfeeder team member is already on Claude Desktop, and AI adoption is actively underway across the company. The Director comes in to accelerate and structure what has already begun with a team that is engaged, tooled up, and ready to move faster. You'll directly manage a team of 7: a BizOps & Data Warehouse team (5 people) with an Engineering Manager reporting to you, and a Revenue Operations team (2 people). - The EM handles day-to-day technical leadership of the engineering team; you set the direction, prioritise the roadmap, and ensure the team is working on the highest-impact problems. - Revenue Operations also sits under this role, the systems and data behind our revenue engine, and it's one of the first places to put AI to work. - The broader mandate, though, is AI-led operational transformation across the company. Qualifications - Practical, commercially aware and technically fluent. - Deep hands-on experience using AI and building AI-enabled workflows, agents or internal tools that solve real problems. - Highly proficient with agentic coding tools such as Claude Code or Codex. - A genuine drive to lead AI transformation across a company. - Technical fluency to design solutions, challenge engineers and judge build vs. buy decisions. - A strong operations mindset: spot friction, prioritise ruthlessly, simplify, and turn ideas into solutions. - Comfort working with data, and clear communication across both technical and business audiences. - Readiness to own Revenue Operations (CRM, pipeline, forecasting). - Readiness to set direction and build a small team. Requirements - Experience building or leading an internal AI enablement, AI operations or automation function. - Salesforce experience, particularly around CRM architecture, reporting, routing and revenue process design. - Experience with tools such as Claude, ChatGPT, Codex, Zapier, Make, n8n, Retool, Clay, Salesforce automation, BI tools or internal workflow platforms. - Hands-on with open-source agent platforms such as OpenClaw or Hermes. - Experience working with distributed or remote-first teams. - Experience partnering with Legal, Security or Compliance teams on responsible AI or data governance. - Previous experience in a scale-up environment where processes, systems and operating models are still evolving. Benefits - The chance to work with a very knowledgeable, high-achieving and fun team. - An international, diverse, dynamic and committed work environment. - The opportunity to work remotely, with a flexible work schedule. - Mental Health support with Auntie. - Personal budget for home office equipment. - Personal development plans as standard, allowing you to develop the skills you think are most important to succeed in your role, as well as regular 1-1s and group training. - Transparent compensation practices with salary range and key compensation details provided before the first conversation.