Senior Generative AI Solutions Engineer

2 weeks ago

Sunnyvale, CA, United States Madison-Davis, LLC Full time

Join a leading global financial technology organization that is heavily investing in AI innovation. We are expanding our engineering teams to develop next-generation Generative AI solutions. We have multiple openings for engineers at various experience levels, ranging from emerging talent to seasoned architects, across key areas such as AI platform engineering, chatbot development, and data engineering for AI-driven systems.

Why You Should Consider This Opportunity

This is your chance to be part of a dynamic enterprise committed to advancing AI strategies that enhance client experiences and boost internal productivity on a large scale. You will become a member of a high-performing engineering team dedicated to delivering enterprise-grade AI capabilities across different business sectors.

Your Responsibilities

  • Design, implement, and optimize production-grade AI and LLM-based systems for enterprise applications.
  • Contribute to model fine-tuning, prompt optimization, and efficient training workflows.
  • Create APIs, microservices, and SDKs for both internal and client-facing AI products.
  • Collaborate with engineering and data teams to operationalize AI solutions and enhance MLOps/LLMOps processes.
  • Work cross-functionally to design and deliver robust, scalable AI integrations.

Your Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
  • 4+ years of hands-on experience in Python development.
  • Strong understanding of Generative AI, LLMs, and pertinent model architectures.
  • Experience with NLP, model training, and fine-tuning workflows.
  • Proficient in Linux environments and modern DevOps methodologies.

Preferred Skills (Please Highlight These on Your Resume)

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

What We Offer

  • Be part of an organization that is making significant investments in AI and automation initiatives.
  • Work with cutting-edge technologies in a data-rich large-scale environment.
  • Collaborate with top engineers and data scientists who are driving AI innovation in the financial technology sector.
  • Opportunities for career advancement across diverse teams and initiatives.

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