New York University
AI Solutions Architect
Docker
Kubernetes
NoSQL
Edtech.com's Summary
New York University is hiring an AI Solutions Architect to lead the technical strategy, design, and implementation of AI and machine learning solutions across university business units and research initiatives. This role drives the full lifecycle of AI projects, ensuring solutions are secure, scalable, and aligned with institutional goals while collaborating with diverse stakeholders and integrating advanced AI technologies.
Highlights
- Lead design and deployment of AI/ML solutions for university business and research needs.
- Develop and optimize data pipelines, model integration, and evaluate AI platforms and vendor solutions.
- Expertise required in Python, TensorFlow, PyTorch, scikit-learn, SQL/NoSQL databases, Docker, Kubernetes, Git, Jenkins, and Terraform.
- Strong knowledge of cloud AI/ML services and their integration capabilities.
- Minimum 7 years of experience in software engineering, data analytics, or related fields.
- Bachelor’s degree required in Computer Science, Engineering, Data Science, or similar; Master’s preferred.
- Exceptional problem-solving and communication skills to engage technical and non-technical stakeholders.
- Experience in managing AI projects with attention to security, scalability, and legal compliance.
- Annual base salary range of $180,000 to $220,000 in compliance with NYC Pay Transparency Act.
- Preferred experience deploying AI/ML in higher education or research environments.
AI Solutions Architect Full Description
Position Summary:
The AI Solutions Architect serves as the highly skilled and experienced AI technical leader responsible for driving the technical strategy, design, and implementation of Artificial Intelligence and Machine Learning (AI/ML) solutions across the university. Bridge the gap between innovative AI concepts and their practical, scalable deployment in university business units and research initiatives. Lead the entire technical lifecycle of AI solutions, ensuring they are robust, secure, and aligned with institutional objectives. Leverage deep technical expertise in designing and optimizing data pipelines, model integration, and evaluating both internal platforms and vendor solutions to deliver production-ready AI capabilities.
Qualifications:
Qualifications:
Required Education:
Bachelor's Degree in Computer Science, Engineering, Data Science, Data/Business Analytics, or related field.
Preferred Education:
Master's Degree Computer Science, Engineering, Data Science, or related field/experience.
Required Experience:
7+ years Progressive experience in software engineering, Programming, data pipelines, data analytics, or related fields, or equivalent combination of education and experience.
Required Skills, Knowledge and Abilities:
Excellent collaboration and interpersonal communication skills. Strong understanding of AI/ML concepts, methodologies, and applications. Proven ability to gather program in AI. Deep expertise in Python and standard ML/Data Science libraries (e.g., TensorFlow, PyTorch, scikit-learn). Expert-level knowledge of data warehousing, database technologies (SQL/NoSQL), and data modeling for machine learning. Strong understanding of containerization and orchestration technologies (e.g., Docker, Kubernetes). Solid grasp of DevOps/MLOps principles and tools (e.g., Git, Jenkins, Terraform). Comprehensive knowledge of major cloud provider AI/ML services and their integration capabilities. Exceptional Problem-Solving Ability: Ability to analyze complex, ambiguous business and technical requirements and design clear, pragmatic solutions. Strong Communication & Interpersonal Skills: Proven ability to communicate effectively with highly technical teams (developers, data scientists) and non-technical stakeholders (leaders, business users). Ability to foster long-term partnerships with functional 'process owners' and academic leaders. This role requires a commitment to the full lifecycle of an AI solution—not just the initial build Leadership & Influence: Ability to lead technical design discussions, drive consensus, and influence technical direction without direct authority. Ability to balance the 'open' nature of a global academic institution with the stringent security and legal constraints required for AI. Proven track record of navigating the technical and ethical trade-offs between global research collaboration and data privacy requirements. Curiosity & Adaptability: Passionate about staying current with the rapidly evolving AI and cloud technology landscape and quickly adapting new technologies. Attention to Detail: Meticulous approach to defining architectures, ensuring security, scalability, and long-term maintainability over experimental speed. Proven ability to identify, document, and mitigate technical and legal risks before any solution is moved to production.
Preferred Skills, Knowledge and Abilities:
Experience deploying AI/ML tools in a higher education or research setting. Deep knowledge of AI/ML workflows and tools.
Additional Information:
Bachelor's Degree in Computer Science, Engineering, Data Science, Data/Business Analytics, or related field.
Preferred Education:
Master's Degree Computer Science, Engineering, Data Science, or related field/experience.
Required Experience:
7+ years Progressive experience in software engineering, Programming, data pipelines, data analytics, or related fields, or equivalent combination of education and experience.
Required Skills, Knowledge and Abilities:
Excellent collaboration and interpersonal communication skills. Strong understanding of AI/ML concepts, methodologies, and applications. Proven ability to gather program in AI. Deep expertise in Python and standard ML/Data Science libraries (e.g., TensorFlow, PyTorch, scikit-learn). Expert-level knowledge of data warehousing, database technologies (SQL/NoSQL), and data modeling for machine learning. Strong understanding of containerization and orchestration technologies (e.g., Docker, Kubernetes). Solid grasp of DevOps/MLOps principles and tools (e.g., Git, Jenkins, Terraform). Comprehensive knowledge of major cloud provider AI/ML services and their integration capabilities. Exceptional Problem-Solving Ability: Ability to analyze complex, ambiguous business and technical requirements and design clear, pragmatic solutions. Strong Communication & Interpersonal Skills: Proven ability to communicate effectively with highly technical teams (developers, data scientists) and non-technical stakeholders (leaders, business users). Ability to foster long-term partnerships with functional 'process owners' and academic leaders. This role requires a commitment to the full lifecycle of an AI solution—not just the initial build Leadership & Influence: Ability to lead technical design discussions, drive consensus, and influence technical direction without direct authority. Ability to balance the 'open' nature of a global academic institution with the stringent security and legal constraints required for AI. Proven track record of navigating the technical and ethical trade-offs between global research collaboration and data privacy requirements. Curiosity & Adaptability: Passionate about staying current with the rapidly evolving AI and cloud technology landscape and quickly adapting new technologies. Attention to Detail: Meticulous approach to defining architectures, ensuring security, scalability, and long-term maintainability over experimental speed. Proven ability to identify, document, and mitigate technical and legal risks before any solution is moved to production.
Preferred Skills, Knowledge and Abilities:
Experience deploying AI/ML tools in a higher education or research setting. Deep knowledge of AI/ML workflows and tools.
Additional Information:
In compliance with NYC's Pay Transparency Act, the annual base salary range for this position is USD $180,000.00 to USD $220,000.00. New York University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/training, key skills, internal peer equity, as well as, market and organizational considerations when extending an offer. This pay range represents base pay only and excludes any additional items such as incentives, bonuses, clinical compensation, or other items.
NYU aims to be among the greenest urban campuses in the country and carbon neutral by 2040. Learn more at nyu.edu/nyugreen.
NYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. All interested persons are encouraged to apply at all levels.
NYU aims to be among the greenest urban campuses in the country and carbon neutral by 2040. Learn more at nyu.edu/nyugreen.
NYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. All interested persons are encouraged to apply at all levels.
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