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Bounteous

Forward Deployed Engineer, Gen AI

New York, NYfull timemidAdded 2 days ago

About this role

Bounteous is hiring a Forward Deployed Engineer to embed with a major investment bank's Fixed Income team in New York and design, build, and deploy production-grade generative AI solutions. This is a hands-on, client-facing role requiring strong software engineering skills, practical gen AI experience, and the ability to translate complex financial workflows into AI-enabled systems while navigating regulatory requirements.

What you'll do

  • Embed with Fixed Income business teams to understand workflows, pain points, and identify high-value AI opportunities
  • Design, prototype, and build generative AI applications using Python, OpenAI/Claude Agent SDKs, RAG, and agentic frameworks
  • Partner with traders, operations, risk, and compliance teams to translate business requirements into technical solutions
  • Build retrieval pipelines across structured and unstructured financial data including research, trade data, and internal repositories
  • Develop evaluation frameworks to test AI outputs for accuracy, hallucination risk, compliance alignment, and user trust
  • Guide AI solutions from concept through controlled production adoption while supporting user adoption and feedback loops

What they're looking for

  • Python and modern software engineering practices
  • Generative AI frameworks (OpenAI, Claude Agent SDK, comparable LLM APIs)
  • Prompt engineering, grounding, context management, and output validation
  • Retrieval-augmented generation, vector databases, and embeddings
  • Enterprise API integration, databases, and cloud services
  • Business requirement translation and stakeholder management
  • AI evaluation frameworks and model performance monitoring
  • Enterprise AI governance and regulatory compliance
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Bounteous

Website
bounteous.com
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Likely interview questions

  • Walk us through a time you built a generative AI application from concept to production—what were the key technical decisions and business trade-offs?
  • How would you approach identifying and prioritizing AI use cases with a Fixed Income business team that may not fully understand LLM capabilities and limitations?
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