Senior GenAI Engineer
National Basketball Association (NBA) · New York, NY
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- On site
- Full-time
- $200,000 / year
- New York, NY
Job highlights
- Lead Generative AI development for NBA operations.
- Build foundational AI infrastructure and products.
- Design and fine-tune LLMs for enterprise challenges.
- Integrate AI tools with existing NBA systems.
- Drive AI literacy and adoption across the organization.
About the role
Senior GenAI Engineer
The NBA’s Enterprise Generative AI team is seeking a highly skilled and visionary Software Engineer to lead the development, deployment, and scaling of cutting-edge Generative AI applications that reimagine how our internal IT systems and business operations function. This role offers a unique opportunity to build foundational AI infrastructure and products that directly impact the way the NBA operates across departments—ranging from IT automation and support to business intelligence and productivity enhancement.
As a technical thought leader, you’ll drive forward the use of large language models (LLMs) and foundational models (FMs), designing and fine-tuning bespoke AI solutions tailored to enterprise challenges. You’ll collaborate across IT, business, and product teams to identify transformative use cases and implement scalable AI-first workflows that unlock new value.
Why Join Us
- Be at the forefront of enterprise AI transformation within one of the most recognized sports and media organizations in the world.
- Drive high-impact initiatives that blend technology, data, and user experience to shape the future of work across the NBA.
- Work with cutting-edge tools and LLM platforms in a collaborative, fast-paced, and forward-thinking environment.
Major Responsibilities
- Design and Develop: Architect and implement robust, scalable Generative AI systems using LLMs to solve enterprise-wide challenges in automation, knowledge discovery, and workflow acceleration.
- Model Development & Optimization: Fine-tune LLMs and foundational models to enterprise-specific data, optimizing for performance, latency, and relevance.
- Enterprise Integration: Seamlessly integrate AI tools into existing systems such as ServiceNow, GitHub, Tableau, SharePoint, and other platforms.
- Infrastructure Leadership: Define, build, and maintain scalable MLOps and LLMOps infrastructure for efficient model deployment, monitoring, and lifecycle management.
- Operational Efficiency: Develop automated AI-driven tools for internal support, IT ticketing systems, and operational efficiency improvements.
- AI Productization: Lead the creation of proof-of-concepts and transition them into production-grade AI features with cross-functional adoption plans.
- Best Practices & Governance: Champion ethical AI practices, security compliance, and responsible AI principles across the development lifecycle.
- AI Evangelism: Collaborate with internal stakeholders to promote AI literacy and adoption through demos, training sessions, documentation, and strategic influence.
- Innovation Watch: Stay up-to-date on industry trends, research papers, and emerging models to continuously improve and innovate NBA’s internal AI capabilities.
- Impact: Work closely with business and technology leaders to identify high-impact AI use cases and develop plans to address them.
Required Education/Professional Experience
- Educational Background: Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or related discipline.
- Enterprise Engineering Experience: Minimum 3 years in applied AI/ML roles, ideally in enterprise contexts. Experience integrating ML solutions with platforms such as ServiceNow, GitHub, or cloud-based environments.
Required Skills/Knowledge Attributes
- AI/ML Expertise: Deep understanding of Generative AI, LLMs, NLP, Transformers, and model fine-tuning techniques. Practical experience building and deploying models using frameworks like Hugging Face, PyTorch, or TensorFlow.
- Infrastructure & MLOps: Strong knowledge of cloud AI infrastructure (AWS/GCP/Azure), containerization (Docker/Kubernetes), and ML pipelines. Hands-on with tools like MLflow, Weights & Biases, or SageMaker.
- Software Engineering: Strong full-stack engineering skills (Python, JavaScript, Node.js, React, etc.) and background in building APIs and microservices.
- Data Fluency: Proficient in building ETL pipelines, managing structured/unstructured datasets, and using SQL and NoSQL systems. R experience is a bonus.
- Communication & Strategy: Exceptional communication skills to present technical topics clearly to executives, and a strategic mindset to align AI concepts and projects with business objectives.
Full Time Benefits
Employees currently are eligible to receive an annual discretionary performance bonus, awarded at the sole discretion of the Company and subject to any terms and conditions set by the Company. Employees and/or eligible dependents may be eligible to participate in the following Company-sponsored employee benefit programs: medical; dental; vision; life/AD&D insurance; short- and long-term disability; fertility and family-forming assistance; wellbeing allowance; educational assistance; mental health coaching/therapy; tax advantaged accounts such as HSA and healthcare/dependent care FSAs; a 401(k) retirement plan; and time off benefits that include vacation, sick time, and personal days.
Key skills/competency
- Generative AI
- LLMs
- Machine Learning
- NLP
- Python
- Cloud Infrastructure
- MLOps
- Software Engineering
- Data Engineering
- Technical Leadership
Skills & topics
- Generative AI
- LLM
- Machine Learning Engineer
- Python
- NLP
- Transformers
- MLOps
- AI Engineer
- Enterprise AI
- Software Engineer
How to get hired
- Tailor your resume: Highlight your AI/ML expertise, LLM experience, and enterprise integration skills, using keywords from the Senior GenAI Engineer job description.
- Showcase your projects: Quantify your achievements in building and deploying AI models, emphasizing impact on efficiency and business objectives.
- Prepare for technical questions: Be ready to discuss Generative AI concepts, LLM fine-tuning, MLOps practices, and cloud infrastructure.
- Demonstrate strategic thinking: Articulate how you align AI initiatives with business goals and communicate technical ideas to non-technical stakeholders.
- Research the NBA: Understand their mission, values, and how AI can transform a global sports and media organization.
Technical preparation
Practice fine-tuning LLMs on diverse datasets.,Build and deploy ML models using cloud platforms.,Develop scalable MLOps/LLMOps pipelines.,Create APIs and microservices with Python.
Behavioral questions
Describe a complex AI problem you solved.,How do you stay updated on AI trends?,Explain AI concepts to a non-technical audience.,How do you prioritize AI projects with business goals?
Frequently asked questions
- What are the key responsibilities for a Senior GenAI Engineer at the NBA?
- As a Senior GenAI Engineer at the NBA, your key responsibilities will include designing and developing scalable Generative AI systems using LLMs, fine-tuning models for enterprise data, integrating AI tools with existing platforms like ServiceNow and GitHub, leading MLOps infrastructure, and promoting AI literacy across the organization.
- What specific AI/ML expertise is required for this Senior GenAI Engineer role at the NBA?
- The NBA seeks a Senior GenAI Engineer with deep expertise in Generative AI, Large Language Models (LLMs), Natural Language Processing (NLP), Transformers, and model fine-tuning. Practical experience with frameworks like Hugging Face, PyTorch, or TensorFlow is essential.
- What kind of educational background is preferred for the Senior GenAI Engineer position at the NBA?
- The NBA prefers candidates for the Senior GenAI Engineer role to have a Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a closely related discipline.
- How does the NBA approach remote work for its Senior GenAI Engineer role?
- For eligible employees, the NBA offers the option of working remotely one day per week for the Senior GenAI Engineer position. This provides a hybrid work arrangement, balancing in-office collaboration with remote flexibility.
- What are the primary goals of the Enterprise Generative AI team at the NBA?
- The primary goal of the NBA's Enterprise Generative AI team is to reimagine internal IT systems and business operations through cutting-edge Generative AI applications. This includes driving IT automation, enhancing business intelligence, and improving productivity across various departments.
- What are the expected software engineering skills for the Senior GenAI Engineer at the NBA?
- The NBA expects Senior GenAI Engineers to possess strong full-stack engineering skills, particularly in Python, JavaScript, Node.js, and React. Experience in building APIs and microservices is also a key requirement.
- What kind of impact can a Senior GenAI Engineer expect to have at the NBA?
- A Senior GenAI Engineer at the NBA can expect to have a significant impact by building foundational AI infrastructure and products that directly influence how the organization operates. You'll work on high-impact initiatives that shape the future of work across the NBA.
- Does the NBA require on-site work for the Senior GenAI Engineer position?
- The NBA offers eligible employees the option of working remotely one day per week. Therefore, this Senior GenAI Engineer position is considered hybrid, requiring some on-site presence, likely in New York or New Jersey given the vaccination policy mention.