Senior Backend Engineer (Go) - AI Generation Pipeline

Job Description

What You Will Do

• Design and scale Go microservices that manage the full lifecycle of an AI generation.
• Optimize our ConnectRPC services and asynchronous pipelines (Kafka, SQS) to handle long-running, resource-intensive inference without compromising platform stability.
• Build the backend logic behind advanced features, including multimodal orchestration across images, video, audio, 3D and vector.
• Work with AWS to manage large data throughput and integrate with high-performance storage and compute clusters.
• Collaborate with external providers and Product to bridge the gap between model output and production user experience.
• Make and document architectural decisions on concurrency, queueing, backpressure, and failure handling as the pipeline scales.
• Improve reliability and latency across the generation path, and own the observability needed to see both clearly.
• Own quality end-to-end: code review, testing strategy, and on-call readiness for the services you build.
• Integrate new frontier models into production workflows quickly and safely.
• Contribute to the technical direction across the wider backend platform, not only your own services.
• Stay current with distributed systems practice, AI infrastructure, and model-serving developments.

What You Will Need

• Extensive experience building and scaling backend services in Go in high-traffic, high-volume SaaS environments.
• Proven ability to design distributed microservice architectures, including asynchronous processing (Kafka, SQS), low-latency service communication (gRPC, ConnectRPC, or GraphQL) and long-running or resource-intensive workloads with queueing, backpressure, and retry strategies.
• Deep AWS knowledge (EKS, S3, Lambda) alongside solid relational database skills, ideally Postgres: schema design, query performance, and handling growth.
• Strong production discipline: observability, performance profiling, debugging live systems, code review, and automated testing.
• Comfortable owning and documenting architectural decisions. Good written and spoken English.
• Strong sense of ownership over the reliability and quality of the systems you build, and over whether they actually perform for users rather than just read well.
• Pragmatic and self-directed; defines an approach without a fully specified brief, balances engineering quality against product goals, and ships dependable systems at pace rather than over-engineering.
• Strong written communicator who documents decisions by default, takes direct feedback well, and works effectively in a distributed team with limited real-time overlap.

Nice to Have

• Media processing experience such as video transcoding, audio synthesis, or vector manipulation.
• AI infrastructure experience: model serving at scale, GPU-accelerated workloads, integrating third-party or open-source generative models into production, and cost optimization for compute-heavy jobs.
• Background in a startup or other fast-moving, distributed environment, with an interest in helping shape product direction.

Please note: You must already be living in Australia or New Zealand to be considered for this role.