AE
Show more filters
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
