Senior Staff Engineer, AI Governance

Visa Visa · Fintech · Foster City, CA

Senior Staff Engineer role focused on AI Governance at Visa, building an 'AI Observatory' product to ensure responsible and trustworthy AI systems. The role involves designing, developing, and maintaining AI governance services, ensuring compliance with ethical and regulatory requirements, and working with generative AI technologies. It requires experience in software development, big data, ML, and agentic frameworks, with a focus on model lifecycle management, bias, fairness, and explainability.

What you'd actually do

  1. You will design, develop, and maintain scalable and reliable AI governance service.
  2. You will apply robust architectural principles to create effective and efficient solution.
  3. You will work closely with interdisciplinary teams, including data scientists, product managers, and legal experts, to ensure compliance of AI systems with ethical standards and regulatory requirements.
  4. You will be instrumental in developing an advanced Responsible AI platform utilizing the latest Generative AI technology.
  5. You will address the evolving challenges in AI governance, ensuring the creation of responsible and trustworthy AI solutions.

Skills

Required

  • software development
  • big data
  • machine learning processes
  • design, coding, testing, debugging, deployment, and monitoring of applications
  • Python
  • Java
  • Golang
  • React.js
  • Next.js
  • predictive models
  • ML libraries
  • Hadoop
  • Spark
  • Docker
  • Kubernetes
  • Airflow
  • agile environment
  • ML, AI and Generative AI model and applications development
  • agentic frameworks
  • OpenAI or Anthropic or Llama models
  • Retrieval-Augmented Generation (RAG) techniques
  • Pre-Training
  • Fine-Tuning
  • Reinforcement Learning
  • Model Bias
  • Fairness
  • Model Explainability
  • Model Drift

Nice to have

  • Google Cloud Vertex AI
  • AWS SageMaker
  • Azure Machine Learning Studio
  • mentoring and leading engineering teams

What the JD emphasized

  • AI Governance
  • Responsible AI
  • Trustworthy AI
  • AI Observatory
  • ethical standards
  • regulatory requirements
  • Generative AI technology
  • Model Bias
  • Fairness
  • Model Explainability
  • Model Drift

Other signals

  • AI Governance
  • Responsible AI
  • AI Observatory
  • ML model lifecycle
  • ethical standards
  • regulatory requirements