AI Solutions Engineer

At Sabio Group, we are dedicated to fostering an environment where employees thrive. Since 1998, we have built a dynamic culture that is both challenging and fun, driven by a team of ambitious, knowledgeable individuals who are passionate about leading the CX revolution. We are seeking creative, resourceful people to join our fast-growing organisation, where you will have the opportunity to develop your skills and contribute to a culture of continuous learning. We work with some of the world’s largest organisations across various industries, delivering exceptional digital customer experiences through our unique blend of expertise, technology, and insight. As one of Europe’s fastest-growing providers of CX transformation solutions, we are committed to sustainability, diversity, and inclusion, ensuring our workforce reflects the diverse society we serve. Join us and help shape the future of customer experience.

We are currently looking for a passionate and enthusiastic AI Solutions Engineer. We look for people with the right cultural fit having what it takes to drive our business forward. We also look for people who are keen to develop new knowledge and skills, because our growth is ultimately dependent on yours. You will play an important role in driving change within our business, joining a department that is continually on a journey of change.

• Deliver customer facing AI solutions as part of a project delivery team, owning engineering tasks from design through build, test, release, and handover.
• Build agentic AI solutions and concepts aligned to customer use cases, including tool use, orchestration, planning and execution loops, and workflow automation.
• Rapidly develop proof of concepts, prototypes, and MVPs to validate value, then evolve them into production ready solutions where required.
• Engineer and integrate AI capabilities into broader systems including APIs, services, data sources, identity and access, observability, and operational tooling.
• Translate requirements into clear technical deliverables, including estimates, dependencies, risks, and implementation approaches.
• Apply strong software engineering discipline including clean code, testing, version control, code review, documentation, and secure coding practices.
• Support customer workshops and delivery ceremonies, communicating design decisions, trade offs, and progress to technical and non-technical stakeholders.
• Implement appropriate guardrails and responsible AI controls covering privacy, safety, transparency, auditability, and human oversight.
• Contribute to delivery acceleration through reusable components, templates, reference implementations, and internal tooling improvements.

• Mid to senior level software engineering experience with strong hands on capability in Python and or another modern language, producing production quality code.
• Practical experience building solutions using generative AI and LLMs, including prompt and flow design, retrieval augmented generation, tool and function calling, evaluation, and iteration.
• Experience applying agentic AI patterns such as multi step orchestration and tool usage, planning and execution workflows, state management, and safety approaches appropriate to the use case.
• Experience delivering within a customer project environment, including managing ambiguity, iterative delivery, deadlines, and stakeholder engagement.
• Strong integration skills including REST APIs, authentication and authorisation concepts, error handling, performance, and reliability considerations.
• Familiarity with cloud native engineering principles in a platform agnostic way, including environments, configuration, CI CD, logging and monitoring, and secrets management.
• Strong communication skills, able to explain technical concepts and decisions clearly to mixed audiences.
• A quality mindset covering testing strategy, maintainability, documentation, and operational considerations.
• Experience with Cognigy or similar conversational AI and intelligent automation platforms.
• Experience in conversational AI, contact centre, or customer experience automation use cases.
• Familiarity with agent and LLM frameworks and tooling, including orchestration frameworks, vector databases, and evaluation tooling.
• Awareness of governance and assurance practices such as prompt security, data privacy, model evaluation, red teaming, and audit trails.
• Experience building reusable accelerators to improve delivery speed and consistency across projects.