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Honeydew

Senior Software Engineer - Platform

Posted 15 hours ago
5-10 years experience
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AI Summary

You will build and optimize the platform infrastructure to enable feature teams to ship faster while hardening data security and compliance. You will also collaborate with engineering management to plan and execute platform projects using agentic engineering methods.

The Mission 💪

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.

About Honeydew 👋

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.

The Opportunity 📈

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.

What You'll Build (Your First 6 Months) 🛠

  • 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!

How You'll Make an Impact

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.

What We're Looking For

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'll Thrive Here If…

  • 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.

Our tech stack

  • 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

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