AI Ops Engineer

AI Ops Engineer Working Arrangement: Remote (Flexible) Outside IR35 FTC OR Freelance/Contract My client is a high-growth, product-led SaaS business operating at scale across the UK, supporting high-volume, business-critical workflows. The business is investing in becoming more data-driven and operationally efficient, with AI as a key lever for improving productivity, reducing cost, and enhancing customer experience. This is a fixed-term project role focused on embedding AI into core operations. The Role I am looking for a commercially minded AI Operations consultant to identify inefficiencies, design and implement AI-driven solutions, and embed AI as a core operational capability. You will work cross-functionally across Customer Operations, Marketing, Training, Finance and Strategy to automate workflows, reduce manual overhead, improve reporting, increase support efficiency, and leverage internal data platforms to drive intelligent automation, with a focus on delivering measurable improvements in cost, efficiency, and operational performance. Core Responsibilities ● Define and execute an AI operations roadmap, prioritising initiatives based on ROI and business impact ● Identify inefficiencies and design AI-driven workflow automation across core systems (e.g. CRM workflows, support ticket triage, reporting automation) ● Build and deploy automation pipelines using tools such as Zapier/Make, LLM APIs, and API/webhook integrations ● Leverage internal data platforms to create event-driven workflows, predictive insights, and AI-enabled reporting ● Establish governance frameworks, ensure GDPR compliance, and develop internal AI playbooks ● Drive adoption and training across teams to embed AI into day-to-day operations Required Experience ● Proven experience delivering AI-driven workflow automation in a SaaS or product-led environment ● Strong experience across core SaaS operational systems, ideally covering CRM, support, billing and product analytics (Salesforce, Zendesk, Zuora, Pendo) ● Strong API integration capability and experience with automation tooling ● Proficiency in Python and SQL ● Experience working with LLM APIs and prompt engineering Great to have ● Additional exposure to data platforms such as Databricks or ThoughtSpot ● Understanding of RAG pipelines and vector databases (Hands-on experience across several of the above systems is beneficial) Commercial & Operational ● Experience operating in a SaaS environment with a strong understanding of core metrics (MRR, churn, retention). Demonstrated ability to deliver measurable ROI from automation initiatives, combined with strong cross-functional stakeholder management. This is an opportunity to shape how AI is embedded into a scaled SaaS platform — not as experimentation, but as core operational infrastructure.