Evoke mission
Our mission is to delight players with world-class betting & gaming experiences.
At evoke, we power global brands including William Hill, 888 and Mr Green.
We are building the next generation of intelligent gaming platforms—where AI enhances every layer of the customer journey. From real-time personalization and responsible gaming safeguards to automated operations and decision-making, our systems transform complex processes into intuitive, trusted experiences.
Our platforms are designed for reliability, compliance, and scale, operating across multiple jurisdictions where trust is paramount. By combining deep domain expertise with advanced AI capabilities, we empower our teams and partners to deliver faster, smarter, and more responsible gaming experiences worldwide.
About The Team
We’re hiring AI engineers to help us transform how digital gaming platforms operate and interact with customers at scale. We leverage generative AI and agentic systems to power smarter customer experiences, automate complex operational workflows, and enable real-time decision-making across our platforms.
Delivering meaningful AI-driven experiences in a regulated, high-stakes environment is not just about integrating the latest LLMs. Producing accurate, compliant, and trustworthy outcomes requires building robust foundations—AI guardrails, domain-aware orchestration, human-in-the-loop controls, and resilient deployment practices. We are focused on creating a reliable backbone for AI agents to safely interact with our ecosystem, ensuring consistency, auditability, and performance across jurisdictions.
Our team is building the core infrastructure for agentic AI within Evoke: enabling AI agents to connect seamlessly to our platforms, developing reusable agentic tools, and exposing standardized Model Context Protocols (MCPs) that can be leveraged across teams and use cases. This foundation will unlock a new generation of intelligent automation and customer interaction.
What you’ll be doing
- Lead and grow a cross-functional team of AI engineers and QA specialists, owning the end-to-end delivery of AI-powered and agentic systems in production.
- Define and drive the technical and execution strategy for the team, balancing innovation with reliability, compliance, and scalability in a regulated environment.
- Own the development of the AI platform backbone, including agent connectivity, Model Context Protocols (MCPs), and reusable agentic tools that enable AI agents to safely interact with our systems.
- Guide the design and implementation of AI solutions end-to-end—from experimentation and prototyping to production deployment and continuous improvement.
- Ensure high engineering and quality standards across the team, embedding best practices in software development, testing, CI/CD, and observability.
- Work closely with product, design, and business stakeholders to define priorities, align on success metrics, and deliver impactful AI-driven capabilities.
- Establish robust evaluation and validation frameworks for AI systems, ensuring outputs are accurate, consistent, compliant, and trustworthy.
- Drive a strong culture of ownership, accountability, and continuous improvement across both engineering and QA disciplines.
- Mentor and develop team members, supporting both technical growth and leadership capabilities, while fostering collaboration between developers and QA.
- Lead incident management and root cause analysis for production issues, ensuring learnings are translated into systemic improvements.
- Stay at the forefront of AI, LLMs, and agentic system design, bringing relevant innovations into the team while maintaining a pragmatic, production-first mindset.
- Stay up to date with emerging practices in AI testing and evaluation, bringing new approaches to validate generative AI and agentic systems effectively.
- Promote a strong quality culture across the team, advocating for best practices in testing, observability, and responsible AI deployment.
Requirements
Required Experience for Success
- Bachelor’s or Master’s degree in Computer Science or a related field.
- 5+ years of experience in software engineering, AI/ML, or related fields, with at least 2–3 years leading cross-functional engineering teams.
- Proven experience delivering complex, production-grade systems end-to-end, ideally in distributed or high-scale environments.
- Strong technical background in AI/ML systems, including experience with LLMs, NLP, or agentic frameworks, and the ability to guide architectural decisions.
- Solid software engineering foundations, including system design, code quality, testing strategies, CI/CD, and observability.
- Experience building or integrating APIs, microservices, and platform-level capabilities.
- Understanding of AI system challenges such as non-determinism, evaluation complexity, latency, and reliability—and how to design systems that mitigate them.
- Experience working in regulated or high-trust environments is a strong advantage.
- Strong leadership skills, with a track record of building, mentoring, and scaling high-performing engineering teams.
- Excellent communication and stakeholder management skills, with the ability to align technical and non-technical audiences.