Middle Python Software Engineer (AI/ML Backend)

About us We are a product R&D company that creates solutions for the dynamic iGaming ecosystem. Our mission is to build cutting-edge platforms that reinvent the iGaming industry. About the team We are a focused engineering team of 5 to 9 people at a multi-product tech SaaS company. We work across personalization, recommendation, fraud detection, and some GenAI, through real- time, near-real-time, and batch pipelines. The team is a blend of Python backend engineers, ML engineers, QA (manual and automation), a data engineer, and data scientists. Our shared mandate is to take experimentation from our data scientists and turn it into robust, production- grade systems, either as standalone services or integrated into wider platforms. The role You will build and operate production backend systems alongside senior engineers and a hands- on engineering manager, owning your work end to end and growing into the harder problems. The systems you work on are either part of a larger SaaS backend or run as standalone services: batch and event-driven pipelines, stream consumers, feature stores, REST APIs, scheduled jobs and background workers. Responsibilities • Design and build production Python services: APIs, stream consumers, pipelines, feature stores, scheduled jobs, background workers • Write and tune the SQL and schemas these services depend on • Uphold engineering standards: code quality, testing, observability, deployment discipline • Productionize data scientists' experimentation into reliable services • Diagnose and fix problems in production • Contribute to design discussions and the implementation approach for the systems you work on • Review code and help raise the bar for what the team ships • Take part in the team's on-call rotation for the systems you build and operate Requirements • 3+ years of backend engineering experience • Strong Python: async, data processing, and working with Redis, Kafka and database clients • Deep database skills — non-trivial SQL, query plans, index design, transactions and isolation levels, and concurrency • Experience across relational and non-relational stores, and when to choose which • Good working knowledge of Docker and CI/CD, enough to partner well with DevOps • Experience owning a service in production Nice to have • Graph databases (Neo4j or similar) • PostgreSQL internals: MVCC, autovacuum and bloat, partitioning, connection pooling • PySpark, Databricks • Kubernetes • Experience building LLM-powered systems, including the vector stores behind them • Fraud detection, recsys, or personalization systems experience • Prometheus and Grafana • SaaS or high-scale product domain experience Why join us • Work on high-scale, high-throughput backend systems • Broad range of technologies, stacks, and problems • Take experimentation from data scientists and turn it into production systems • A strong engineering culture that values technical depth and ownership • A technically strong environment with a modern stack and a mature Agile culture • High autonomy, decision-making authority, and close cooperation with leadership • Room to contribute your own ideas for improvement and see them implemented • Flexibility through hybrid and remote working • A distributed team across Dubai and Europe • Discretionary annual bonus, based on individual, team, and company performance • Comprehensive medical insurance • Annual flight allowance • Visa sponsorship • Annual leave • Learning and conference budget • Company-paid AI coding assistant Interview stages 1. HR interview (30 minutes) — initial conversation about your experience, career goals, and cultural fit 2. Technical interview (1 hour) — in-depth technical interview covering relevant skills 3. Technical design interview (1.5 hours) — system and database design 4. Final interview (30 minutes) — a discussion with the hiring manager, focusing on role- specific competencies and alignment with company values 5. Reference check & job offer Show more Show less

• 3+ years of backend engineering experience • Strong Python: async, data processing, and working with Redis, Kafka and database clients • Deep database skills — non-trivial SQL, query plans, index design, transactions and isolation levels • Experience across relational and non-relational stores, and when to choose which • Good working knowledge of Docker and CI/CD, enough to partner well with DevOps • Experience owning a service in production

• Design and build production Python services: APIs, stream consumers, pipelines, feature stores, scheduled jobs, background workers • Write and tune the SQL and schemas these services depend on • Uphold engineering standards: code quality, testing, observability, deployment discipline • Productionize data scientists' experimentation into reliable services • Diagnose and fix problems in production • Contribute to design discussions and the implementation approach for the systems you work on • Review code and help raise the bar for what the team ships • Take part in the team's on-call rotation for the systems you build and operate