Our mission is to ensure that no one in the world has to suffer from a treatable skin disease because of an access issue ever again.
Honeydew is building a platform for hundreds of millions of people globally to access expertise and science-backed skin treatments, from prescription to retail. Our tech-forward dermatology experience helps people with chronic skin conditions access licensed specialists, FDA-approved treatment, and ongoing support in record time. Honeydew is the future of skin health — digitally native, scientifically rooted, integrated end-to-end, and powered by AI.
Our feature teams can only move as fast as the platform underneath them, and we want to help them move faster. As a Platform Engineer, you’ll contribute to the work that makes our platform stronger, from moving our data layer onto RDS, to tightening security and compliance across our multi-account AWS organization, to building tooling that speeds up every team shipping on top of it. You’ll review and test your teammates’ work, and partner with feature teams and other stakeholders to shape what our platform can do next.
By day 60: Standardize and optimize our logging for AI-supported troubleshooting across the platform.
Day 61-180: Implement processes and infrastructure for AI agents to autonomously open PRs to resolve dependency vulnerabilities and other issues
And more platform and security-related improvements TBD!
Build the platform. You'll work with the engineering manager to identify and plan projects, then execute them using agentic engineering methods.
Harden data and security. You'll deliver the migration, security, and compliance work that keeps our data stores, APIs, and cloud infrastructure safe and reliable.
Enable the feature teams. You'll assist other teams with data and security requests, and review other engineers' code, so everyone ships faster on a solid foundation.
The Non-Negotiables:
Object-oriented programming language with strong data and architecture skills — production experience building backend services and APIs, and current best practices in data modeling and system architecture
Platform security — you've secured platform-layer components, including data stores, APIs, and cloud infrastructure, applying current best practices for access control, encryption, and audit logging
Infrastructure and automation — hands-on experience building and operating production infrastructure with infrastructure as code (CDK, Terraform, or CloudFormation) and CI/CD pipelines
The Nice-to-Haves:
Experience in healthcare setting, or another heavily regulated domain
Experience building and using custom agents
Experience with Typescript, AWS, serverless functions, PostgreSQL
You make a plan and execute to that plan and timeline.
You identify and report timeline issues early.
You identify and champion opportunities to improve the ecosystem you work in.
You keep up with current best practices, including AI-assisted engineering.
You give direct, useful feedback in code review.
You request and give help when needed.
You write things down so the next engineer can rely on them.
Languages: TypeScript, Python, SQL
Frontend: React, Redux Toolkit, Material UI, Tailwind CSS, Vite, Next.js
Backend: Node.js on AWS Lambda, GraphQL (AWS AppSync, Apollo), REST (API Gateway), event-driven architecture (EventBridge, SQS, SNS), authentication (Cognito)
Data: PostgreSQL (RDS), DynamoDB, OpenSearch, S3
Infrastructure: AWS (multi-account, Control Tower, CloudFormation, IAM, SSM, CloudWatch, CloudTrail), Terraform, Serverless Framework, Docker, LocalStack, Git, CI/CD on Bitbucket Pipelines and GitHub Actions
Analytics: Databricks, dbt, Amplitude
AI: OpenAI and Anthropic APIs, Cursor
Testing: Vitest, Jest, Playwright
Du prägst die technische Richtung beim Neuaufbau einer Kubernetes-Plattform auf Bare Metal, entwickelst Plattformkomponenten und Automatisierung und verbesserst Stabilität, Architektur und Betrieb.
Build the core AI platform for an AI-native trading experience, developing high-performance Rust services, reliable model and tool orchestration, secure APIs, and safe infrastructure for trading actions.
Own and evolve the AWS platform, security, CI/CD, and reliability foundations, delivering infrastructure improvements that strengthen production systems and help product teams build, test, and deploy faster.
Design and operate governance, security, deployment, and monitoring foundations for AI platforms, enabling trusted data models, responsible AI adoption, and sustainable infrastructure across business teams.
Own and evolve cloud infrastructure, deployment systems, and production reliability, enabling teams to ship product changes safely while shaping architecture and resolving complex distributed-systems issues.
