Head, AI Engineering

Success Academy Charter Schools•New York, NY

2d•$280,000 - $300,000•Onsite

About The Position

Success Academy is seeking a results-driven Head, AI Engineering to join our Technology team. Working within our central Network office and reporting to the CTO, you will be responsible for establishing and maintaining a comprehensive information security and privacy program tailored to the unique needs of a K-12 school environment. This critical role focuses on safeguarding student and staff data, proactively managing cybersecurity risks, and ensuring strict compliance with all relevant regulations in an educational setting. The Success Academy Technology team manages a modern technology environment built around cloud and SaaS-based applications, and operates networking and in-school technologies across 59 school locations.

Requirements

5+ years of experience in AI/ML development, with a strong portfolio of successfully delivered AI projects.
7+ years of experience in a leadership or management role, leading and mentoring AI or software development teams.
Proven experience in designing and implementing end-to-end AI/ML solutions in a production environment.
Experience with various machine learning techniques (e.g., supervised, unsupervised, reinforcement learning) and deep learning frameworks (e.g., TensorFlow, PyTorch).
Familiarity with cloud platforms preferable AWS cloud platform and working knowledge of GCP and their AI/ML services.
Experience with MLOps principles and tools for model versioning, deployment, and monitoring.
Expertise in programming languages commonly used in AI development, such as Python.
Strong understanding of data structures, algorithms, and software design principles.
Deep knowledge of machine learning algorithms, statistical modeling, and data science methodologies.
Excellent leadership, communication, and interpersonal skills, with the ability to inspire and motivate a team.
Ability to translate complex business problems into technical AI solutions.
Strong problem-solving abilities and a data-driven approach to decision-making.
Passion for education and a commitment to Success Academies' mission.
Strong understanding of Google Cloud AI tools (Vertex AI, AutoML, BigQuery ML, Document AI, and Generative AI APIs).
Knowledge of open-source AI/ML frameworks (TensorFlow, PyTorch, LangChain, Hugging Face, LlamaIndex).

Responsibilities

Lead and mentor a team of AI developers, fostering a culture of innovation, collaboration, and continuous learning.
Architect, design, and oversee the development of scalable and robust AI/ML models and applications.
Define and implement best practices for AI development, MLOps, model deployment, and performance monitoring.
Collaborate closely with product managers, data scientists, and other engineering teams to identify opportunities for AI integration and ensure alignment with organizational goals.
Manage the full lifecycle of AI projects, from conceptualization and research to deployment and ongoing optimization with production support.
Stay abreast of the latest advancements in AI, machine learning, and deep learning, evaluating and recommending new technologies.
Provide management with high-level updates and understanding of the technological advancements and road map accomplishments.
Ensure the quality, security, and ethical considerations of all AI solutions.
Communicate technical concepts and project progress effectively to both technical and non-technical stakeholders.
Contribute to the strategic vision for AI within Success Academies and help shape the future of our technological landscape.
Work with the Cloud Engineering team to be able to deploy products in AWS infrastructure using Terraform and multiple other deployment strategies.
Ensure responsible AI use, bias mitigation, and compliance with data privacy laws (FERPA, GDPR, etc.). Also, have an understanding of AWS cloud security framework applied to AI governance.
Act as a trusted advisor to executives, school administrators, and non-technical stakeholders.
Present AI concepts, project updates, and business impacts in a clear and compelling manner.
Translate technical AI capabilities into practical use cases that drive adoption.
Work cross-functionally with engineering, data science, and education experts to ensure AI solutions are user-centric.