Technisch engineer.

AI Engineer - Gaming Innovation GroupJoin to apply for the AI Engineer role at Gaming Innovation Group. Our AI, Analytics & Data Science team is the strategic core of our mission to become the undisputed AI‑driven leader in the iGaming industry. You will join a growing, agile team of data scientists and ML engineers at the heart of GiG's most ambitious strategic initiatives. You will be a lead engineer on our state‑of‑the‑art GiG Assistant platform, powered by Google Gemini , and will be instrumental in transforming our entire software development lifecycle. If you are a world‑class engineer who wants to build high‑impact, enterprise‑grade AI solutions, this role is for you. Core Mission To be a lead hands‑on developer and strategic engineer for GiG’s internal AI platforms. Your mission is to contribute to our cutting‑edge AI architecture, build the tools that accelerate our engineering teams, and act as a powerful champion for AI adoption across the entire organisation. You'll work alongside a dedicated team of engineers and analysts to achieve these goals. Architect and build robust, scalable data pipelines to continuously ingest knowledge from our core internal systems (JIRA, Confluence, Slack, Google Drive, Codebases). Enterprise‑Grade Quality: AI‑Enhanced Software Development Lifecycle (SDLC) This includes piloting, rolling out, and supporting the central management of rules and best practices for AI‑powered IDEs, ensuring consistency, quality, and robust QA oversight for all AI‑assisted development. Develop Model Context Protocol (MCP) Servers: Lead the development and management of our custom MCP servers, which provide tailored, real‑time context to our AI development tools, ensuring they understand our proprietary codebases. Measure Engineering Impact: Collaborate with engineering leads to track KPIs (e.g., DORA metrics) that measure the direct impact of your work on developer productivity and code quality. Upskill Your Colleagues: Develop and deliver practical training sessions, workshops, and documentation to empower all GiG employees to use AI tools effectively and responsibly. Experience: Proven experience as a software or machine learning engineer, with a strong focus on building and deploying AI/ML‑powered applications in a production environment. Generative AI Expertise: Deep, hands‑on experience with LLMs, vector databases, and building advanced RAG architectures (e.g., Expert‑level proficiency in Python and its associated AI/ML ecosystem (LangChain, LlamaIndex, TensorFlow, PyTorch). Cloud & MLOps: Strong experience with a major cloud platform (GCP, Azure, or AWS) and a firm grasp of MLOps principles for deploying, monitoring, and managing models in a production environment. Demonstrated ability to architect, build, and consume APIs and integrate disparate data sources to create cohesive systems. Hybrid working model International Health Insurance Mid‑Senior level Full‑time Engineering and Information Technology