AI Practitioner

Godel Technologies Europe is a software engineering company headquartered in Manchester, UK, with 1.5k+ employees across Europe and 5 offices in Poland (Lodz, Wroclaw, Gdansk, Bialystok, Warsaw) employing 1.2k people. They deliver agile at scale and build mission critical products for leading UK brands such as SHELL Energy, the Gym Group, Secret Escapes, ao.com, DealTrak, and theidol.com.

Must have:

• Strong software engineering background (6+ years)
• Solid understanding of AI/ML fundamentals (LLMs, tokens, embeddings, RAG, fine-tuning) and their practical trade-offs
• Strong prompt engineering: systematic prompting, structured outputs, scenario adaptation
• Hands-on GenAI tool experience in delivery contexts
• Ability to work independently and deliver reliably (Competent level per framework)
• Experience in workflow analysis and AI solution design
• Strong communication across audiences: recommendations, sessions, training
• Awareness of responsible AI concerns: privacy, hallucinations, safe usage
• Broad delivery understanding to spot AI opportunities across adjacent roles

Nice to have:

• Experience building AI-enabled automations, internal helpers, or lightweight end-to-end workflows
• Experience integrating AI via APIs or configuring custom assistants / GPT-style workflows
• Familiarity with multiple AI product categories (coding assistants, conversational AI, productivity copilots)
• Ability to evaluate practical applicability of new AI tools across the broader ecosystem
• Experience delivering live demos, workshops, or pair-working sessions to support adoption
• Experience creating playbooks, guidelines, reports, or reusable learning materials

• Identify high-value AI opportunities through workflow analysis
• Design AI solutions: select tools, techniques, prompting approaches
• Configure and use GenAI tools across delivery workflows
• Build lightweight automations and API-based integrations
• Support adoption via demos, pair-working and hands-on enablement
• Deliver tailored training and knowledge transfer
• Present recommendations to stakeholders and manage expectations
• Apply responsible AI practices to mitigate data leakage, hallucinations and bias
• Document and share AI practices to raise organizational capability