Winnow was founded with a simple belief that food is too valuable to waste.
Winnow develops technology used by a growing number of organizations to cut food waste in their operations. Our digital…
📋 Job Overview
Winnow is seeking a Platform Engineer (DevOps) to join our small, senior platform team. We are on a mission to eliminate food waste at scale using AI-powered technology in hospitality kitchens. The role involves designing and building the platform for agentic engineering, managing infrastructure as code, and supporting data science and AI workloads.
🏢 About Winnow
Food waste costs the world over $1 trillion a year. At Winnow, we're on a mission to change that — bringing AI-powered technology into hospitality kitchens to help eliminate waste at scale, with an ambition to save our clients $1 billion annually. We started in London in 2013 and have grown into a global team spanning multiple countries, working across 90+ countries and 3,500+ sites.
🎯 The Role
You'd be joining a small, senior platform team. We work closely with the engineers who rely on our platform daily, so communication and empathy for their day-to-day pain points matter as much as technical depth. This is a team that's comfortable with ambiguity, a lot of what we're building (especially around agentic engineering) doesn't have a playbook yet, so we value people who can define the problem as well as solve it.
✅ Key Responsibilities
Design and build the platform for agentic engineering at Winnow: guardrails, golden paths, evals and cost controls.
Build and run the golden paths for humans too, the paved routes our engineers use to ship to production.
Own our AWS and GCP infrastructure as code (Terraform with Terragrunt).
DevOps: Work with development teams to improve how we deploy.
Support our data science and AI workloads: Airflow pipelines, SageMaker, and GPU scheduling.
Debug the hard things across clouds, databases, containers, network and edge.
📌 Required Qualifications
You are likely to be degree-educated having completed studies in Computer science, computer engineering, information technology, or a related field.
Solid AWS experience, plus Linux and networking fundamentals.
Infrastructure as code, Terraform or OpenTofu.
Containers and orchestration: ECS, Kubernetes, or both.
Bash, plus Python or Go at a level where you'd happily own a service.
CI/CD pipelines you've built and maintained.
You use AI coding assistants and agents day to day, and you have views on where they help, where they don't, and what would have to be true before you'd trust one with something that matters.
⭐ Desirable Experience
Observability (OpenTelemetry, Grafana, ELK, New Relic)
GitOps (ArgoCD or Flux)
Airflow, SageMaker or MLflow
LLM infrastructure such as inference serving, evals and LLM/ MCP gateways
