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Lead Generative AI Engineer

Lead Generative AI Engineer

Madison-Davis, LLCSan Francisco, CA, United States
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We’re supporting a major global financial technology organization that’s making significant investments in AI innovation. They’re scaling their engineering teams across North America to drive development of next-generation Generative AI solutions. Multiple openings are available for engineers at varying levels — from early-career developers to senior leads and architects — across areas like AI platform engineering, chatbot development, and data engineering for AI-driven systems.

Why This Role

This is a chance to be part of a global enterprise that’s putting real resources behind AI strategy — building tools, platforms, and models that impact client experiences and internal productivity at scale. You’ll join a high-performing engineering group that’s delivering enterprise-grade AI capabilities across multiple business lines.

What You’ll Do

  • Build and enhance production‑grade AI and LLM‑based systems for enterprise applications.
  • Contribute to model fine‑tuning, prompt optimization, and training workflows.
  • Develop APIs, microservices, and SDKs for internal and client‑facing AI products.
  • Collaborate with engineering and data teams to operationalize AI solutions and support MLOps / LLMOps processes.
  • Partner cross‑functionally to design and deliver reliable, scalable AI integrations.

What You Bring

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent practical experience).
  • 4+ years of hands‑on Python development experience.
  • Strong understanding of Generative AI, LLMs, and related model architectures.
  • Experience working with NLP, model training, and fine‑tuning workflows.
  • Solid grasp of Linux environments and modern DevOps practices.

    • Nice to Have (Highlight These on Your Resume)

  • Hands‑on experience with frameworks like Flask, Django, or FastAPI.
  • Familiarity with Python libraries such as numpy, pandas, scikit‑learn, matplotlib, or opencv.
  • Experience deploying AI solutions using cloud services like Azure OpenAI, AWS Bedrock, AWS Sagemaker, or Google Vertex AI.
  • Background in AI / ML lifecycle management — MLflow, Databricks, or Dataiku.
  • Understanding of MLOps or LLMOps principles.
  • Exposure to TensorFlow or PyTorch.
  • Experience integrating AI models into enterprise or regulated environments.
  • Familiarity with containerized cloud environments (Docker, Kubernetes).
  • Version control experience with GitHub or Bitbucket.
  • Bonus : experience working with conversational AI platforms (e.g., Copilot Studio, Kore.ai, Amelia).
  • Experience collaborating with software development teams to embed AI into core applications.

    • What’s In It for You

  • Join an organization that’s putting real investment behind AI and automation initiatives.
  • Work on cutting‑edge technology in a large‑scale, data‑rich environment.
  • Collaborate with top‑tier engineers and data scientists driving AI innovation in financial technology.
  • Opportunities for career growth across multiple teams and projects.

    • Seniority level

    Mid‑Senior level

    Employment type

    Full‑time

    Job function

    Information Technology

    Industries

    Staffing and Recruiting

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