Tech.

The role is hybrid in Malta, Mondays are mandatory Main Responsibilities: Design and evolve scalable, secure, and resilient distributed systems while defining architectural standards and shared components across the platform. Contribute hands-on to key backend projects to ensure alignment between architecture and implementation. Mentor engineering teams on system design, coding practices, and development methodologies. Lead technical initiatives that improve engineering quality, tooling, and efficiency. Work closely with stakeholders to gather requirements, provide accurate estimates, and ensure architectural decisions support long-term business and technical goals. Support long-term planning for scalability, performance, observability, and maintainability. Guide teams on production readiness, deployment processes, and operational reliability. Participate in hiring and managing engineering teams while helping define career paths and performance processes. Desired experience: 8+ years in a similar architectural or senior engineering role. Strong backend expertise in Java with the modern Spring ecosystem, relational databases, Docker, and Kubernetes. Proven experience building distributed systems with high scalability, security, and reliability requirements. Hands-on MySQL knowledge, including data modeling and performance tuning. Practical experience with containerized environments, cloud-native infrastructure, and CI/CD pipelines. Experience leading or managing engineering teams. Strong system design skills and ability to guide complex architectural decisions. Understanding of software security principles. Experience collaborating with cross-functional and leadership stakeholders. Ability to translate requirements into architectural solutions and provide accurate estimates. Fluent English and strong communication skills. Nice to have (not mandatory): familiarity with frontend technologies, third-party integrations, AWS or other cloud providers, and high-throughput or real-time systems.

Engineering Team Manager – iGaming Payment Platforms   Form part of an international iGaming organisation Lead high-impact engineering teams across the payment platform Drive technical strategy, scalability, and product excellence   Hybrid in Stockholm Full-time, Permanent Salary: Circa €100K (depending on experience)   A leading and well-established iGaming company is seeking an Engineering Team Manager to oversee technical strategy and execution across platform and payment domains. This is a senior leadership opportunity for someone who thrives in high-traffic, performance-critical environments and is passionate about building resilient systems, scalable architectures, and high-performing engineering teams.   This role combines hands-on technical competence with strategic leadership. You will shape technical direction, mentor engineering teams, and collaborate closely with product, compliance, and payment stakeholders to deliver best-in-class gaming experiences.   Your Role Set the technical vision and engineering roadmap across multiple product and payment platform verticals Lead, mentor, and scale engineering teams across backend, integration, frontend, and DevOps Guide teams responsible for secure, stable, and compliant payment flows across markets and providers Partner closely with senior product and business stakeholders to translate requirements into scalable, high-availability technical solutions Drive excellence in code quality, architecture, test automation, and operational reliability Establish engineering best practices across development, testing, deployment, and incident management Build and maintain relationships with internal stakeholders and external payment partners Promote a culture of accountability, ownership, continuous improvement, and technical innovation Oversee hiring, capability development, and performance management for hybrid and distributed teams   What You Bring 8+ years of hands-on software engineering experience, including at least 2+ years in technical leadership or engineering management Strong understanding of payment integrations, APIs, and transaction-processing systems (advantageous but not mandatory) Proven ability to manage and scale engineering teams in complex, high-availability environments Deep knowledge of modern engineering practices, including microservices, CI/CD, cloud infrastructure, and event-driven architecture (Kafka, Redis, or similar) Experience working within agile, product-led organisations Strong communication skills and ability to collaborate across technical and business domains Structured, proactive mindset with a drive to simplify, optimise, and improve engineering processes Background in iGaming, fintech, sports betting, or other high-throughput transaction systems is strongly preferred

My client is a leading provider of AI-powered customer service tools, specializing in sports betting & gaming sector. They partner with global operators to deliver intelligent, automated support that enhances player experience and operational efficiency. They are now expanding the U.S. engineering capability to support client integrations and AI performance excellence across the region. Why Join? · Be part of the team shaping the future of AI-driven customer service in gaming and sports · Work directly with world-class engineers, data scientists, and product leaders · Blend hands-on technical work with strategic product impact · Competitive salary, performance incentives, and potential equity participation · Fully remote work options available within the U.S. The Role: This role is primarily a full-stack developer position, with a strong focus on AI evaluation and client integration. You’ll work closely with Product, Engineering, and Client Solutions teams to: · Deploy and integrate the AI platform into client stacks · Build, test, and monitor custom connectors, APIs, and data flows · Design and automate evaluation systems to measure and improve AI response quality · Contribute directly to the continuous improvement of the AI and platform architecture This role is ideal for a technically versatile engineer who enjoys working across code, data, and AI quality systems and who thrives in a fast-moving, high-impact environment. Key Responsibilities: Client Integration & Engineering · Prompt engineering (design and implement client specific prompts) · Model selection (evaluation and selection of LLM configurations for client specific context) · Build and maintain integrations between the AI platform and client systems (PAMs, CRMs, ticketing, chat, data APIs, etc.) · Support deployment, configuration, and validation of new AI environments for enterprise customers · Develop and maintain reusable SDKs, API wrappers, and automation scripts to streamline onboarding · Troubleshoot and resolve technical issues in collaboration with the Product and Solutions teams AI Evaluation & Quality · Design and run automated and manual evaluation tests for AI responses (accuracy, tone, latency, compliance) · Build dashboards and tools to monitor AI quality and performance across client deployments · Partner with the Senior Product Manager to translate evaluation findings into roadmap improvements · Collaborate with the AI engineering team to test new model versions and fine-tuning experiments · Document findings and maintain clear visibility of performance metrics for internal and client stakeholders About You: My client are seeking a full-stack engineer who can work comfortably at the intersection of software engineering, applied AI, and client delivery. Requirements: · 4+ years’ experience in full-stack engineering or ML · Strong proficiency in Node.js with Ruby on rails experience a major plus · Understanding of APIs, data pipelines, and system integrations · Familiarity with LLMs or conversational AI platforms (OpenAI, Anthropic, etc.) · Experience with evaluation frameworks (precision/recall, prompt-based testing, or human-in-the-loop QA) · Strong analytical and troubleshooting skills; ability to debug across systems · Excellent communication skills and comfort working across distributed global teams Bonus / Nice-to-Have: · Experience with gaming, sports betting, or high-volume transactional systems · Exposure to observability tools (e.g., Datadog, Grafana) or experiment tracking frameworks · Interest in applied AI safety, ethics, and model performance evaluation