Head of Automation Engineering

Who are we?

Welcome to Multiple (https://themultiple.com), your go-to iGaming service provider. We’re here to empower iGaming operators, allowing them to thrive in such a volatile industry. Our years of expertise, cutting-edge technology, and passion for delivering extraordinary player experiences make us the right choice for any company looking to elevate their success. We offer a range of iGaming offerings such as; Gaming Services, Casino Marketing, Sportsbook Marketing and Operations, Creative, Data and B.I, Operations (CS, RPF, KYC), VIP Management, Acquisition, Social Media, Content, Product, Legal and Compliance.

The Role:

At themultiple, we are redefining the iGaming industry by embedding intelligence into every layer of our operations. As Head of AI Automation & Agentic Systems, you will architect and lead the group’s end-to-end AI automation capability — from bare-metal infrastructure through to autonomous, multi-agent workflows that power our Casino, Sportsbook, Marketing, Operations, and Compliance functions.

This is a hands-on leadership role for someone who can move fluently between evaluating open-source model benchmarks, designing cost-optimised inference stacks, and steering the business case for AI-driven transformation at the executive level. You will own the full lifecycle: build the platform, select and deploy the models, identify the highest-value use cases, and drive measurable ROI across a diverse group of companies.

Key Responsibilities:

Infrastructure & Platform

• Configure and manage cloud-based AI service integrations (e.g. OpenAI, Anthropic, Google) for appropriate use cases, while actively reducing third-party dependency for core operational workflows.
• Deploy and operate self-hosted open-source models (e.g. Llama, Mistral, Qwen, Phi families) using serving frameworks such as Ollama or vLLM, across cloud or on-premise environments.
• Design lightweight orchestration layers that connect both hosted and self-hosted AI services to internal systems, data sources, and operational workflows.
• Define and enforce security, access control, and data governance standards for all AI systems — with particular attention to data residency and sovereignty when handling sensitive player and operational data.
• Implement monitoring and observability across all AI integrations — tracking uptime, latency, token consumption, and cost per workflow.

Model Selection & Evaluation

• Maintain a structured evaluation framework for benchmarking open-source models (Llama, Mistral, Qwen, Gemma, Phi, and emerging releases) against closed-source alternatives across quality, speed, and total cost of ownership.
• Default to open-source, self-hosted models for operational use cases — reserving third-party API calls for tasks where the capability gap genuinely justifies the cost and dependency.
• Match model capabilities to specific business tasks — knowing when a self-hosted 8B model is the right call and when a frontier API is unavoidable.
• Design retrieval-augmented generation (RAG) architectures that ground model outputs in company data, reducing hallucination and improving task relevance.
• Stay current with the rapidly evolving open-source landscape and translate new model releases into concrete operational improvements across the group.

Cost Optimisation & Governance

• Own the AI cost model across the group: track spend per workload, establish unit economics, and enforce budget guardrails — with open-source self-hosting as the primary lever for reducing ongoing operational cost.
• Apply cost-reduction techniques including model routing (self-hosted vs. third-party tiers), prompt compression, caching strategies, and batching architectures.
• Produce clear ROI reporting for each AI initiative, linking automation output to measurable business outcomes (headcount efficiency, revenue impact, risk reduction).
• Build and maintain a vendor and model evaluation process that continuously challenges reliance on paid APIs — migrating workflows to self-hosted alternatives as open-source capability matures.

Leadership & Collaboration

• Build a lean, high-calibre automation engineering team from the ground up — defining the hiring profile, team structure, onboarding standards, and ways of working suited to a fast-moving, output-focused function.
• Lead the team with a bias for delivery: set clear priorities, remove blockers, and maintain a culture where working systems ship regularly rather than ideas circulate indefinitely.
• Establish engineering standards for the team covering code quality, agent design patterns, testing practices, documentation, and operational handoff.
• Translate complex agentic AI concepts into clear business language for non-technical stakeholders and executive audiences.

Requirements:

• 7+ years experience  in software engineering or infrastructure roles, with at least 3 years focused on AI/ML systems in a production environment.
• Prior experience in a technical leadership or principal engineer capacity is required.

Nice to Have:

• Experience in iGaming, fintech, or another regulated, data-intensive industry.
• Familiarity with compliance automation use cases: AML monitoring, responsible gambling tooling, regulatory reporting.
• Experience working across a group or holding company structure spanning multiple products and jurisdictions.
• Contributions to open-source AI projects or published technical writing on AI systems design.

What we offer:

• Attractive remuneration package
• Health insurance cover from the first day of work
• Wellness benefit (after probation)
• Optician/Spectacle and Blue Lens Benefit (after probation)
• Breakfast/lunch all week
• Monthly snacks allowance
• Training support
• Modern office facilities
• Dog-friendly workplace
• Exciting Company Events
• Monthly Beer Fridays
• Eur1,000 Refer a friend bonus
• Relocation package (if required)
• One day birthday holiday
  

You should not apply if ...

• You want a normal 9-5 job. This role is not easy & requires an all-in mentality. We are looking for team members who will put in the work that others won't.
• You cannot take constructive feedback.
• You cannot handle stress and pressure.
• You have the mindset of "Quick Money", this is a marathon, not a sprint.
• You do not embody our core values.