Qualified

Senior Software Engineer, Backend – AI Core

Qualified

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Salary

💰 $170,000 - $240,000 per year

Job Level

Senior

Tech Stack

AWSCloudETLGoJavaScriptPostgresPythonRDBMSReactRubyRuby on RailsSQL

About the role

  • Develop and maintain scalable, high-performance backend systems foundational to our product's functionality.
  • Determine the best ways to incorporate LLMs, embeddings, and other AI technologies into Qualified’s platform.
  • Architect and execute robust ETL pipelines for managing and standardizing data from diverse sources to support RAG model training and inference.
  • Ensure the core functionality of the product is stable, scalable, well-maintained, and continuously improving.
  • Own features end-to-end from ideation through coding, testing, deployment, monitoring, and customer rollout.
  • Collaborate closely with customers to gather immediate feedback and refine the platform.
  • Mentor fellow engineers and champion product-focused engineering standards and excellence.

Requirements

  • 5+ years of experience building modern web applications, with a recent focus on leveraging AI/ML technologies.
  • Proficiency in programming languages such as Ruby on Rails, JavaScript, Python, or Go.
  • Hands-on experience in AI-driven application development, including experiment setup, dataset curation, model training, offline evaluation, error analysis, deployment, and online evaluation.
  • Strong background in data-focused backend development and ETL processes.
  • Experience working with SQL and RDBMS (PostgreSQL preferred) and data warehousing solutions.
  • Strong software engineering practices, including coding, unit testing, code reviews, and design documentation.
  • B.S. or higher in Computer Science (or equivalent work experience).
  • Experience working with Agile methodologies.
  • Passionate about crafting innovative, user-centric solutions; self-directed, proactive communicator; high curiosity about applied AI.
  • (Nice to have) Background in working with RAG models; knowledge of LLM evaluation metrics (BLEU, ROUGE, MAUVE) and statistical analysis; startup experience; experience architecting applications within a monorepo.