Senior Software Engineer (GCP Infrastructure & Platform)

About Kambi Kambi Group plc is a leading B2B provider of premium sports betting services to licensed gaming operators. Our services provide an end-to-end solution for operators wanting to launch a standalone Sportsbook or bolster their existing offering with an innovative sports betting product. From front-end user interface to customer intelligence, risk management and odds compiling, all built on our in-house developed software, we strive to deliver the ultimate service and solution to our partners. Our vision is to create the world’s leading sports betting experiences, together with our partners. Purpose Be part of a highly skilled, self-organized engineering team building scalable data and machine-learning infrastructure in the cloud. You’ll help design and evolve event-driven data pipelines and model-serving capabilities that power high-value decision-making across the business, working closely with key stakeholders and quantitative analysts to turn complex data into actionable insights and deliver Player and Risk Management products. Key Responsibilities Collaborate with engineers and analysts to design, implement, and maintain cloud-native data and ML services. Build and optimize streaming and batch data workflows with Kafka, dbt/SQL, and related technologies. Develop robust backend components and services in Java/Spring Boot and contribute to model-serving capabilities in Python where appropriate. Contribute to architectural discussions and propose practical solutions in a fast-moving, exploratory environment. Champion best practices in testing, monitoring, and observability to keep data products reliable and secure. Desired Skills & Experience (You don’t need to tick every box, strong skills in several areas plus willingness to learn are what matter most.) Java/Spring Boot expertise (core requirement). Proficiency in Python for data and ML workflows. Hands-on experience with cloud platforms (AWS, GCP, or similar) and modern CI/CD pipelines (e.g., Jenkins, Argo CD). Familiarity with Kafka and dbt/SQL for streaming and transformations. Experience with Spark or similar distributed processing frameworks is a plus. Personal Qualities (Critical for Success) Driven & Self-Motivated – thrives when goals evolve and problems are ambiguous. Communicative & Collaborative – shares ideas openly and builds trust across disciplines. Curious & Adaptive – eager to explore new tools and approaches. Humble & Team-Oriented– values collective achievement in a highly self-organized team. Interested in learning more? Please submit your CV and a cover letter — we’d love to hear from you! #wearekambi Kambi's ongoing commitment to Diversity and Inclusion in the workplace If you require any reasonable adjustment during the recruitment process, please notify your recruiter, who will assist you however they can. Diversity and inclusion is at the heart of who we are and who we aim to be. While we are proud of the positive and inclusive company culture we have created, we know we can do so much more. Kambi constantly evolves its Diversity and Inclusion strategy to ensure it becomes an even more inclusive and positive place to work, with the core management team reaffirming its commitment to delivering on employee feedback. Creating an inclusive environment We believe Kambi's greatest strength is the collective talent of our employees. Kambi is committed to ensuring we create an inclusive work environment where everyone can feel valued, thrive and achieve their potential, regardless of who they are or what their background is. We know that it is only by having a balance of different voices, values and opinions that Kambi is able to be the market leader it is today. #wearekambi

Sana is an AI lab building superintelligence for work. We believe organizations can accomplish their missions faster when teams can effortlessly access knowledge, automate repetitive work, and learn anything with the help of agentic AI. As part of Workday, we are committed to building AI that augments people - not replaces them. We bring this mission to life through two products. Sana Agents provide a seamless way to access all your company’s apps, knowledge, and data, enabling AI agents to do real work so teams can process and act on information at unprecedented scale. Sana Learn is an AI-powered learning hub that combines the simplicity of a modern learning platform with intelligent features like an AI tutor, automated content generation, and interactive apps, making knowledge not just accessible but actionable. We’re a talent-dense, product-obsessed team of engineers and designers from companies like Google, Spotify, Apple, and Databricks, united by deep technical excellence and rapid iteration. Our tools already help over a million people learn and work better across hundreds of leading enterprises - and we’re just getting started. About the Role You'll build the core agent infrastructure that powers Sana's mission to bring superintelligence to work. This is a greenfield opportunity to define how AI agents plan, reason, and execute across enterprise environments—building systems that reliably handle real-world complexity at scale. You'll work at the intersection of agent architecture, context-, tool- and prompt engineering, and production infrastructure. In this role, you will Architect multi-step planning, orchestration, and tool routing for agents Implement code generation agents and sandboxed code execution Engineer memory, state, and context packing/grounding strategies Balance latency, quality, and cost controls for agent execution Develop safe fallbacks, graceful degradation and robust error handling Collaborate with platform and search teams to deliver reusable agent infrastructure Establish safety guarantees and measurable quality improvements About You Basic Qualifications: 3+ years of software engineering experience building production backend or platform systems. 3+ years of experience in TypeScript, with a strong track record of writing reliable, maintainable services. 3+ years of experience with distributed systems, APIs, asynchronous workflows, and service-oriented architecture. 3+ years of experience designing systems with a focus on scalability, reliability, observability, and maintainability. Other Qualifications: Experience building and deploying LLM-powered applications in production. Experience building agent platforms or AI infrastructure. Deep understanding of the low-level details of the OpenAI, Google, and Anthropic LLM APIs, including tool calling, system prompt caching, etc. Familiarity with LLM application patterns, including tool calling, retrieval-augmented generation (RAG), memory and context management, multi-step orchestration, and human-in-the-loop systems. Experience building and running machine learning systems in production, including compiling training and test datasets, building training pipelines, evaluating models, and detecting and handling drift (neural networks, Gaussian models, Thompson sampling, etc.). Experience designing evaluation frameworks for LLM or agent quality and safety, including hands-on use of platforms such as Langfuse or LangSmith. Familiarity with vector databases, prompt and context engineering, and experimentation tooling. Experience working with sandbox environments such as Modal, and designing strict access control models to keep user data safe and encrypted at all times. Experience running services in Kubernetes-based environments on GCP or equivalent cloud platforms. Comfort working with Postgres and Redis in high-throughput, low-latency service contexts. Contributions to open source TypeScript projects. Ability to navigate ambiguity, make strong technical tradeoffs, and drive projects from concept to production. Strong communication and collaboration skills, with the ability to partner effectively across engineering, product, and AI research teams.