Lead Generative AI EngineerMadison-Davis, LLC • Sunnyvale, CA, United States

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Lead Generative AI Engineer

Madison-Davis, LLC • Sunnyvale, CA, United States

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[job_card.full_time]

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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.

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