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AI Developer

Skills
Full-Stack DevelopmentSoftware As A ServiceApache SparkComplex SystemsContextCost EngineeringDatabases
Role

What the job involves

The main requirements, responsibilities and hiring steps.

Requirements

  • 3+ years of professional AI/ML production experience
  • Strong Python proficiency with packaging testing type hints and async
  • Hands-on experience with LangChain LlamaIndex or similar RAG tools
  • Experience with vector databases and embedding models
  • Solid understanding of ML fundamentals including evaluation and fine-tuning decisions
  • Experience building and deploying production APIs such as FastAPI or Flask
  • Familiarity with cloud infrastructure and Docker or Kubernetes
  • Experience with large-scale data processing using SQL pandas Spark or similar
  • Competent with Git and GitHub branching and PR workflows
  • Ability to iterate quickly without sacrificing code quality
  • Exceptional troubleshooting skills in production at scale
  • Ability to keep complex systems simple
  • Previous remote work experience
  • Reliable personal computer and internet access
  • Availability for audio video meetings and Slack during 9 AM to 1 PM EST

Nice to have

  • Builder at heart
  • Self-starter
  • User-focused
  • Full-stack owner
  • Clear communicator
  • Continuous learner
  • Craftsmanship-minded
  • Team player
  • Interested in internal tools

Day to day

  • Build AI-powered internal tools and data-driven systems that improve organizational decisions
  • Work with large-scale behavioral and operational data from 30 million+ websites to create analytics reporting and workflow intelligence
  • Design and deploy RAG systems LLM features and agentic workflows that generate actionable insights for internal teams
  • Build scalable data pipelines and production-grade Python services with logging observability and strong error handling

Hiring process

  • Submit your application
  • Include a cover letter with AI/ML journey
  • Describe your most impactful production AI system
  • Explain what you would build with data from 30 million websites
  • Provide profile links with code samples
  • Include links to research blog posts or open-source contributions
  • Add other profile links if available
  • Tell why you should be considered