17 - Backend Engineer (Python/Scala)

Our client is scaling fast - new features, new customers, new challenges - and their platform processes over 200 million events every day. They build an AI-powered performance product for customer support teams, blending gamification and machine learning to help teams work smarter. You'll join a small, senior engineering team building the next generation of their backend, where Python powers the AI and LLM features (70%) and Scala drives the event-streaming core (30%). This is a hands-on role for an engineer who thrives on both experimentation and production rigour - comfortable prototyping in Python, and confident enough in Scala to ensure everything scales, performs, and holds up under load.

Key Responsibilities

• Design and build RESTful APIs and streaming services powering the product and analytics layers
• Develop features across Python (70%) and Scala (30%), from rapid prototypes to hardened production systems
• Run data pipelines processing hundreds of millions of daily events using Kafka and Akka Streams
• Optimise performance - offload CPU-bound tasks, design batching/backpressure mechanisms, and tune reliability
• Implement security best practices (OWASP) to protect data and user trust
• Work with LLMs (OpenAI, Anthropic, Vertex AI, Groq, DeepSeek) and help shape scalable AI service patterns
• Act as a bridge between the Scala engineers and the AI/Data Science team
• Collaborate with Product Managers and engineers to architect solutions that balance scalability, speed, and cost

Required Skills and Experience

• 3+ years of experience building backend systems with Python and Scala - strong in one, comfortable in both
• Proven ability to design and optimise Python services under load - balancing I/O and CPU-bound processing
• Solid hands-on experience with Kafka, event-driven systems, and streaming architectures
• Familiarity with Akka Streams or other streaming frameworks
• Strong fundamentals in software design: clean APIs, testing, CI/CD, observability
• Experience with data stores such as MongoDB, Elasticsearch, and ClickHouse
• Curiosity about AI/LLM stacks and scalable ML service design
• Collaborative spirit and a growth mindset