Unknown Company

AI Lead Engineer

new york, ny • Posted 1 weeks ago
Onsite Full Time Engineering

We are seeking an experienced and innovative AI Lead Engineer to lead the end-to-end development, implementation, and performance evaluation of Agentic AI solutions.

This role is ideal for a hands-on AI expert with a strong background in machine learning, model deployment, and performance testing.

The successful candidate will play a critical role in delivering intelligent systems that align with business objectives and drive innovation in the financial services domain.

Key Responsibilities

  • Lead the full lifecycle of Agentic AI solution development, from design and implementation to deployment and optimization.
  • Evaluate and select appropriate AI/ML models and frameworks based on project requirements.
  • Develop and implement robust testing strategies to assess model performance, accuracy, and reliability.
  • Collaborate with cross-functional teams including data scientists, software engineers, and business stakeholders to ensure successful delivery of AI solutions.
  • Monitor and fine-tune deployed models to ensure optimal performance in production environments.
  • Ensure AI solutions adhere to security, compliance, and ethical standards.
  • Document development processes, model evaluation metrics, and deployment strategies.
  • Stay current with advancements in AI/ML technologies and recommend innovative approaches to enhance solution capabilities.

Required Qualifications

  • Proven experience in leading AI/ML solution development and deployment.
  • Strong understanding of Agentic AI systems and their practical applications.
  • Proficiency in AI/ML frameworks such as TensorFlow, PyTorch, or similar.
  • Experience with model evaluation, testing, and performance tuning.
  • Familiarity with cloud platforms (e.g., AWS, Azure, GCP) for AI deployment.
  • Strong problem-solving skills and attention to detail.
  • Excellent communication and collaboration skills.

Preferred Qualifications

  • Experience in the banking or financial services industry.
  • Knowledge of MLOps practices and tools for model lifecycle management.
  • Exposure to ethical AI practices and responsible AI frameworks.

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