Mid-level Generative Artificial Intelligence (genai) Search Solutions Developer

Boeing Boeing · Aerospace · Mesa, AZ +2

Develops and maintains GenAI search solutions, including enterprise, semantic, and GenAI search. Involves fine-tuning LLMs and embedding models, optimizing retrieval pipelines, and collaborating with stakeholders. The role balances research-oriented work with scalable system implementation.

What you'd actually do

  1. Design, develop, and maintain features across Enterprise Search, Semantic Search, and GenAI Search platforms tailored to business partners requirements
  2. Fine-tune and evaluate large language models and embedding models for search relevance and retrieval quality
  3. Build and optimize retrieval pipelines including vector search, hybrid retrieval, re-ranking systems, Application Programming Interfaces (APIs) and backend integrations
  4. Collaborate with product and stakeholders to translate requirements into technical solutions
  5. Instrument experiments, measure model performance, and iterate based on user needs and metrics

Skills

Required

  • Bachelor's degree or higher
  • 3+ years of experience in programming languages such as JavaScript, C#, Python, SQL, etc.
  • 1+ years of experience with Angular
  • 1+ years of experience do you have in web-based development, leveraging ReactJS, Redux, JavaScript, TypeScript, HTML, CSS?
  • 1+ years of experience with RESTFUL APIs
  • 1+ years of experience do you have with GitLab, Azure DevOps and CI/CD (Continuous Integration and Continuous Delivery (CI/CD)
  • Experience with Natural Language Processing (NLP) fundamentals including but not limited to word embeddings, attention mechanisms, sequence-to-sequence models, and transformers
  • Experience researching and applying large language and generative AI models

Nice to have

  • Master's degree in Computer Science, Artificial Intelligence, Information Systems or related fields
  • 1+ years of experience with A/B testing and relevance evaluation frameworks
  • 1+ years of experience with cloud infrastructure (Azure, AWS, GCP)
  • Experience with vector databases
  • Experience with to GenAI product development in an enterprise context
  • Experience with enterprise search platforms (e.g., Sinequa, Goldfire, Elastic, Microsoft Search)
  • Experience with machine learning, NLP, or Knowledge Graphs

What the JD emphasized

  • GenAI Search Solutions Developer
  • GenAI Search
  • enterprise context

Other signals

  • GenAI Search platforms
  • fine-tune and evaluate large language models
  • Build and optimize retrieval pipelines
  • scalable system implementation