Platform engineer

We're hiring for a fast-growing AI startup building a cloud-native analytics platform that transforms large volumes of LLM output into structured, queryable intelligence. The system is fully AWS-native, heavily event-driven, and designed to process high volumes of AI-generated data reliably and cost-effectively. We're looking for a Platform Engineer to own and evolve the infrastructure backbone that powers the entire platform. What You'll Be Doing

• Designing and evolving AWS infrastructure (ECS Fargate, Lambda, Step Functions, EventBridge, S3, DynamoDB, Athena).
• Owning container orchestration, task definitions, networking, IAM roles, and VPC architecture.
• Strengthening infrastructure-as-code and CI/CD automation to ensure repeatable, stable deployments.
• Designing event-driven, distributed systems that scale cleanly under load.
• Building monitoring, alerting, logging, and observability systems (CloudWatch, metrics, tracing).
• Driving performance optimisation and cost efficiency across workloads.
• Embedding security principles, least-privilege IAM, and infrastructure resilience from day one.
• Experimenting with AI agents and automation tools to streamline infrastructure management and operational workflows.
• This is a hands-on engineering role - you'll be building and running the systems, not delegating them.

• Strong production experience operating AWS infrastructure at scale.
• Deep familiarity with ECS (or similar container orchestration), Lambda, Step Functions, S3, and EventBridge.
• Strong Docker and container-native deployment experience.
• Infrastructure-as-code (Terraform, CDK, or CloudFormation).
• Experience designing event-driven or distributed systems.
• Solid Python for automation, scripting, or data pipelines.
• Strong production engineering mindset - reliability, monitoring, debugging, scaling.
• Comfort owning infrastructure decisions and being accountable for production workloads.
• Curiosity about AI tooling and automation-driven engineering.