Senior Software Engineer

We’re looking for a Senior Software Engineer to join our R&D team. This is a hands-on, all-around role where you own the entire pipeline — from ingesting hundreds of thousands of requests per second, through streaming and processing, all the way to a data lake. You build it, you run it, you own it.

Why this role is different

• You build it, you run it, you own it. Write the service, define its infrastructure in Terraform, ship it to Kubernetes, and operate it in production. You own systems end to end — backed by a team that works the same way. No handoffs, no throwing code over the wall.
• The whole pipeline is yours. From a request hitting the edge — parsed, streamed through Kafka, processed, persisted, landed in the data lake — it’s yours end to end. You make the architectural calls and you carry them in production.
• Hard problems, real authority over the tools. Holding request-path latency to single-digit milliseconds while ingesting hundreds of thousands of requests per second forces genuine engineering decisions — and you get to make them. We run a modern Go/Kafka/Databricks stack on AWS and EKS, and we change it when the workload demands better, not when a roadmap says so.
• You shape the system and how we build it. We’re early enough that the architecture and the engineering practices are still taking shape — the testing bar, the deployment discipline, the conventions other engineers will inherit. You won’t slot into someone else’s playbook; you’ll help write it. That’s rare leverage, not the 40th patch on a decade of legacy.
  
  

• Languages: Go 1.24+, Python/PySpark
• Streaming: Apache Kafka (Confluent)
• Data Processing: Databricks
• Infrastructure: AWS (EKS, DynamoDB, S3, ElastiCache), Kubernetes, Helm, Terraform
• Observability: Prometheus, Grafana, OpenTelemetry, OpenObserve
• Databases: DynamoDB, Valkey/Redis, PostgreSQL
  
  

• Design, build, and maintain high-throughput, low-latency microservices
• Develop data pipelines feeding our data lake — user feature aggregation, ML training data, and analytics
• Build event streaming systems on Kafka for real-time data processing
• Own infrastructure-as-code (Terraform) and GitOps practices
• Troubleshoot production issues across distributed systems
• Drive architecture decisions and the technical roadmap
  
  

• 5+ years of software engineering experience
• 3+ years with Go in production, high-throughput systems
• Strong experience with distributed systems and microservices architecture
• Experience with message queues / streaming (Kafka, MSK)
• Proficiency with SQL and NoSQL databases (PostgreSQL, DynamoDB, TimescaleDB)
• Solid experience with Kubernetes and container orchestration
• AWS cloud services (EKS, DynamoDB, S3, ElastiCache)
• Understanding of observability (Prometheus, Grafana, distributed tracing)
  
  

• Ad-Tech experience is a big plus
• Experience with real-time ML inference at scale
• Python/PySpark for data pipelines, or DBT / SQLMesh
• Experience with MLOps
• High-scale distributed databases (Aerospike, ScyllaDB)
• Databricks or similar data platforms
  
  

• Independent problem solver who thrives on performance-optimization challenges
• Ownership mentality — you see features through from idea to production and operations
• Comfortable with ambiguity in a fast-moving startup environment
• Strong debugging skills across distributed systems
• Leverages modern AI tools to multiply productivity and code quality
• Effective communicator who can explain complex technical concepts
  
  

• B.Sc. in Computer Science or equivalent practical experience
  
  

• Be part of a global team that’s talented, fun, and driven
• Work-life balance with our flexible hybrid working model
• Free gym membership conveniently located in our building
• Company events, team building, holiday celebrations, and happy hours
• Be part of something that matters — community support & volunteering initiatives