Gaming Innovation Group logo
Full-time
Remote friendly (Newport, Wales, United Kingdom)
Worldwide
Data Analytics

AI Engineer

Department: Technology

Employment Type: Full Time

Location: Malta

Reporting To: Christopher Zerafa



Description

At Gaming Innovation Group (GiG), we are not just participating in the AI revolution; we are leading it. 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.

This is a unique opportunity to become a key architect of our most ambitious AI platforms. 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.




Key Responsibilities

1. AI Platform & Architecture Leadership:
  • Enhance the GiG Assistant: Be a key technical contributor to our state-of-the-art AI platform. You will enhance and scale its sophisticated, enterprise-grade RAG architecture by implementing advanced techniques such as knowledge graphs, RAPTOR, and reranking models to push the boundaries of accuracy and contextual understanding.
  • System Integration: 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: Ensure our AI platforms are secure, monitored, and highly performant, adhering to MLOps best practices.
2. AI-Enhanced Software Development Lifecycle (SDLC):
  • Govern & Implement AI IDE Tooling: You will be central to how our developers use AI. 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.
3. Organisational Enablement & AI Advocacy:
  • Become the Go-To Expert: Act as a primary technical authority on generative AI applications within GiG.
  • Upskill Your Colleagues: Develop and deliver practical training sessions, workshops, and documentation to empower all GiG employees to use AI tools effectively and responsibly.
  • Champion AI Literacy: Evangelise the power of AI across all business units, helping teams identify new and innovative ways to leverage AI to solve their biggest challenges.
  • Within 3 months: You have made significant code contributions to the GiG Assistant platform and are a recognised subject-matter expert on its architecture.
  • Within 6 months: You have successfully led the implementation of a new advanced RAG feature (e.g., a re-ranking model) that measurably improves the Assistant's accuracy, and you have rolled out a new set of governed rules for our AI IDE tools.
  • Within 12 months: Your work is directly contributing to a measurable improvement in our engineering KPIs, and you have successfully trained and upskilled dozens of colleagues, demonstrably increasing AI adoption across the company.





Requirements

  • 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., knowledge graphs, RAPTOR, re-ranking) is essential.
  • Programming: Expert-level proficiency in Python and its associated AI/ML ecosystem (e.g., 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.
  • System Architecture: Demonstrated ability to architect, build, and consume APIs and integrate disparate data sources to create cohesive systems.
  • Problem-Solving: Exceptional analytical and problem-solving skills, with a passion for architecting elegant solutions for complex challenges.



Benefits

  • Great career development opportunities
  • Hybrid working model
  • International Health Insurance
  • Health and Wellbeing Package (350 EUR per year)
  • Birthday Day Off
  • Me Time - 1 day off per year

Apply now
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