# Director of AI Operations **Company:** [Leadfeeder](http://jobs.workable.com/companies/dDk4XyCcipLpDfp3RWP91A.md) **Location:** Remote **Workplace:** remote **Employment type:** Full-time **Department:** Growth Unit [Apply for this job](http://jobs.workable.com/view/83345d4e-d87a-4da2-9550-7e14ebedf8e3) ## Description Leadfeeder turns B2B websites into lead generation engines. Every day, potential buyers visit your website and leave without filling out a form. Leadfeeder reveals which companies are behind that traffic, shows what they care about, and helps teams act while interest is high. By connecting website behavior with company data, intent signals, and automated workflows, Leadfeeder helps marketing and sales teams prioritize the right accounts and turn anonymous traffic into qualified pipeline. We're a remote-first, international team building the next generation of lead generation technology for B2B marketers. Join us and help redefine how B2B companies generate leads from the signals already happening on their website. ### Position Overview 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. This role requires someone who is practical, commercially aware and technically fluent. You do not need to write production code, but you do need to be confident working with engineers, data teams and business leaders to turn operational pain points into well-scoped, AI-enabled solutions that are adopted and trusted. ### What Success Looks Like Success in this role isn't about launching AI experiments. It's about driving adoption of AI workflows that are trusted and actually improve how the business operates. The right candidate will bring structure to AI adoption, identify high-value opportunities, and deliver practical solutions that lift productivity, accuracy and decision-making across our go-to-market teams first, then the wider business. You move fast and pragmatically, shipping in days rather than quarters and iterating with the people who use what you build. ### Responsibilities AI Operations & Transformation - 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. Technical & Delivery Leadership - 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. Revenue Operations - 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. Change Management & Adoption - 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. ## Requirements Few people have led AI transformation at scale yet, so we care more about hands-on capability, drive and what you have actually built than about years on a résumé. - 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, and ready to go deep on Claude Code as our primary stack. You build with agentic tools, you don't just chat with them. - A genuine drive to lead AI transformation across a company, even where the playbook doesn't fully exist yet. - Technical fluency to design solutions, challenge engineers and judge build vs. buy decisions, without needing to write production code. - A strong operations mindset: spot friction, prioritise ruthlessly, simplify, and turn ideas into solutions people actually adopt. - Comfort working with data, and clear communication across both technical and business audiences. - Ready to own Revenue Operations (CRM, pipeline, forecasting), or to get up to speed on it quickly. It's where many of the first use cases will live. - Readiness to set direction and build a small team, plus a pragmatic approach to responsible AI: privacy, security, and a human in the loop where it matters. ### Nice to Have - 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. - A personal knowledge or "second brain" setup you actually run day to day, for example in Obsidian. - Hands-on with open-source agent platforms such as OpenClaw or Hermes, and a habit of trying whatever is newest in the agentic space. - 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 Leadfeeder is committed to transparent compensation practices. All candidates invited to any stage of the interview process will be provided with the salary range and key compensation details for this role before their first conversation with us.