ABOUT BASIS TECHNOLOGIES

Basis Technologies enables every SAP-run business to manage change intelligently, no matter how complex their technology landscape. Our Intelligent Change Management (ICM) solutions, delivered through our Klario platform, harness the collective intelligence of the SAP community to help business and technology change teams explore, plan, and execute business change imperatives.

We are building a dedicated AI Function to deliver intelligent capabilities across our product portfolio. This role sits within that function, working closely with the Klario product team in Budapest.

THE OPPORTUNITY

At the heart of Klario's value proposition is a large and continuously growing knowledge pool, built from real SAP change history across our customer base. When a customer asks how they should approach a particular type of change, Klario needs to search that knowledge pool and return recommendations that are genuinely grounded in what has, and hasn't, worked for similar changes elsewhere. Not a plausible-looking guess.

Building that retrieval capability properly is hard, and it is the single most important part of our product. SAP has specifically asked us to bring this into Klario. We are looking for an AI Engineer who wants to own it: someone who will build, maintain, and continuously improve a retrieval-augmented generation (RAG) system from first principles, not assemble one by wiring documents into an off-the-shelf API and hoping for the best.

Many of the strongest candidates for this role come from an SAP consulting background, contracted out to build for other organisations, moving from project to project without ever seeing the long-term impact of their work. If that sounds familiar, this role is a chance to build one thing, deeply, for a single product, and see the results of your work compound over time.

IN THIS ROLE, YOU WILL

Core focus: retrieval engineering

• Build, maintain, and optimise a RAG system from scratch, covering ingestion, chunking, embedding, indexing, and retrieval, to deliver accurate, trustworthy recommendations to customers

• Implement hybrid retrieval: combining semantic search, metadata and keyword filtering, and reranking across multi-stage retrieval pipelines

• Build pipelines that extract clean, structured metadata from messy source data, for example SAP transport request descriptions, to improve matching and retrieval accuracy

• Build evaluation harnesses that measure retrieval precision against ground truth, and use that data to continuously improve retrieval quality

• Domain validation and continuous improvement

• Design domain validation logic that critically assesses whether retrieved content is genuinely relevant to a customer's specific context, not just semantically similar or superficially plausible

• Design a feedback workflow that allows reviewers to flag and correct retrieval issues, feeding continuously back into the knowledge pool and validation logic

Wider AI platform contribution

• Apply prompt engineering, context engineering, and structured prompt architecture to power AI-driven chatbots and recommendation workflows

• Work with vector database infrastructure to support large-scale semantic retrieval

• Contribute to the centralised evaluation framework used across our AI capabilities, with a focus on the retrieval evaluation component

• Collaborate closely with the Architecture team and the wider AI Function across Budapest and Bracknell

IS THIS OPPORTUNITY FOR YOU?

We are less focused on years of experience and more focused on depth in one specific area: retrieval. If you have genuinely built and debugged a RAG system, not just called an API and hoped for the best, we want to talk to you.

Essential experience and skills:

• Hands-on experience in AI engineering, building production LLM-powered systems, for example AI-powered chatbots or retrieval-based recommendation tools

• Deep, practical experience building RAG systems from scratch, including chunking strategy, embedding model selection, and indexing design

• Solid understanding of hybrid retrieval: semantic search, reranking, and multi-stage retrieval pipelines

• Experience with vector databases for semantic retrieval at scale

• Experience building evaluation processes that measure retrieval quality against ground truth

• Strong prompt engineering and context engineering skills

• Strong software engineering fundamentals: Python, REST APIs, CI/CD pipelines

• Comfortable working in a fast-moving scale-up environment, figuring things out as you go

Desirable skills:

• Experience with graph databases, as a complement to vector-based retrieval

• Experience with agentic workflow patterns: multi-agent orchestration, tool-calling, state management

• Experience building shared AI infrastructure used by multiple product teams

WHAT WE DO

We enable every SAP-run business to manage change intelligently, no matter how complex their technology landscape. Our suite of Intelligent Change Management solutions harnesses the collective intelligence of the SAP community to help business and technology change teams work together to explore, plan, and execute business change imperatives. For over 25 years, we have helped equip, liberate, and champion SAP change heroes at global leaders like Kimberly-Clark, 3M, and Vistaprint.

WHO WE ARE

We have been officially named one of the UK's Best Workplaces by Great Place to Work, for the third year in a row.

We are at an exciting point as we scale from 130+ global employees. We have the foundations in place to grow with purpose, whilst retaining the individual ownership and tangible impact you would expect working in a scale-up organisation.

We are a global team who collaborate across all levels, locations, and departments, whilst individually having the knowledge, expertise, autonomy, and accountability to drive successful outcomes. Our fast-paced environment means we embrace change and communicate effectively to proactively and creatively solve problems.

WHY JOIN US?

Aside from the benefits of role evolution, tangible individual impact, and personal growth that you would expect working in a global scale-up environment, at Basis Technologies we take looking out for our employees seriously.

Benefits include:

• Competitive salary and annual company bonus, awarded in recognition of overall business performance

• Annual leave in line with Hungarian Labour Law, with entitlement increasing over time based on tenure and other qualifying criteria

• Monthly tax-advantaged SZEP Card contribution (16,700 HUF), usable for accommodation and travel, hot meals and restaurants, cultural programmes, and sports and recreation (available from the month following successful completion of probation)

• Tax-free monthly contribution toward public transport costs

• Monthly cafeteria contribution, taxed at a preferential rate

• Enhanced Parental Leave

• Global Flexibility - work from anywhere for up to one month per year

• Learning and Development Budget

• One paid Volunteering Day per year

• Employee Referral Bonus

• Access to 10 qualified Mental Health First Aiders, plus annual MHFA training opportunities