Lead AI Engineer

Title: Lead AI Engineer Location: New York, NY (Hybrid – 4–5 days per week) Employment Type: 12-Month Contract (with option to convert to full-time) Reports To: Chief Technology Officer (CTO) Team: AI Engineering / Enterprise AI Strategy About The Organization This leading philanthropic organization works to ensure better, longer lives for the greatest number of people by focusing on five key areas: the arts, education, the environment, government innovation, and public health. Operating in over 700 cities and 150 countries worldwide, the organization supports ambitious initiatives that accelerate progress, build capacity, and drive measurable, lasting change. They are recognized for a data-driven, outcomes-focused approach to philanthropy. The organization places a strong emphasis on evidence-based decision-making, measurement and evaluation, and continuous learning to maximize the effectiveness of every investment. This culture of disciplined experimentation and agile response allows the organization to address urgent and underfunded global issues quickly and at scale. Internally, the organization operates with the same high-performance standards it champions externally. It fosters a collaborative, innovative, and mission-driven culture, empowering employees to think creatively, work across disciplines, and deliver transformative solutions. Employees are expected to be proactive, resourceful, and committed to excellence in pursuit of the organization’s global mission. Position Summary The Lead AI Engineer will be responsible for architecting, building, and leading the implementation of enterprise-scale AI systems that transform how the organization leverages data, automation, and intelligence across its global operations. Reporting to the CTO, this hands-on technical leadership role will oversee the design, development, and deployment of large language model (LLM) applications, including ChatGPT Enterprise, Glean AgenticAI, and other generative AI solutions. The Lead AI Engineer will bridge applied research and practical engineering—coding, prototyping, and deploying alongside guiding architecture and governance. This person will work closely with business and product leaders to align AI capabilities with organizational priorities, ensuring responsible, secure, and scalable implementation. The ideal candidate combines technical depth, creative problem-solving, and the ability to mentor teams while advancing the organization’s enterprise AI strategy. Top Skills • ChatGPT Enterprise, Glean AgenticAI, and OpenAI API integration • Large Language Model (LLM) architecture, including RAG and vector database frameworks • MLOps, prompt optimization, and AI workflow orchestration (e.g., LangChain, Azure OpenAI, or GCP Vertex AI) • Ability to code and architect simultaneously—bridging deep technical execution with enterprise-level strategy • Communicate with higher EQ, balancing technical leadership with empathy, clarity, and collaboration • Strong collaboration with non-technical and executive stakeholders Key Responsibilities • Architect, design, and implement scalable AI systems leveraging ChatGPT Enterprise, Glean AgenticAI, OpenAI APIs, and custom LLM pipelines • Develop retrieval-augmented generation (RAG) architectures, vector database integrations, and multi-modal workflows • Lead hands-on development, testing, and deployment of AI tools that enhance productivity, knowledge access, and decision-making • Implement and maintain MLOps frameworks for LLM orchestration, model monitoring, prompt optimization, and performance tracking • Partner with product, data, and operations teams to translate business challenges into AI-solutions • Collaborate with IT, Legal, and Data Governance teams to ensure compliance, security, and responsible AI practices • Mentor junior engineers and analysts, fostering a culture of technical excellence and ethical innovation • Evaluate and integrate new generative AI tools to expand the organization’s enterprise AI capabilities • Support AI policy and governance development to ensure systems meet enterprise standards for security, transparency, and accountability Requirements • Education: • Bachelor’s degree in Computer Science, Data Science, Information Systems, or related discipline (Master’s or MBA preferred) • Experience: • 5+ years of experience in AI/ML engineering, including 3+ years in a technical leadership role • Proven expertise with ChatGPT Enterprise, Glean AgenticAI, OpenAI APIs, and large language model (LLM) technologies • Strong programming experience in Python, LangChain, and orchestration frameworks for LLM development • Hands-on experience deploying AI solutions on cloud platforms (Azure OpenAI, AWS Bedrock, GCP Vertex AI) • Skills: • Understanding of vector databases (Pinecone, FAISS, Weaviate) and retrieval-augmented generation architectures • Deep understanding of data privacy, security, and AI governance best practices • Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders Preferred Qualifications • Experience deploying generative AI within regulated or global enterprise environments • Familiarity with AI policy frameworks, governance models, and ISO/IEC 42001 standards • Strong understanding of knowledge management, enterprise search, and retrieval-augmented generation (RAG) pipelines • Experience with AI-powered workflow integration across enterprise tools such as ServiceNow, Salesforce, SharePoint, Microsoft 365, Zapier, Airtable, and Asana • Demonstrated ability to lead geographically distributed technical teams and mentor engineers at multiple levels • Exceptional communication and leadership skills with the ability to influence technical and non-technical stakeholders globally What You’ll Gain Employees are united by a shared mission to create better, longer lives for the greatest number of people. Joining the team means contributing to a data-driven, innovation-focused organization that invests over $3.7 billion annually to advance global change. You will be part of a collaborative environment that embraces experimentation, evidence-based decision-making, and responsible AI innovation. The Lead AI Engineer will have access to cutting-edge technologies and thought leadership in the field, while being mentored by senior leaders and given the opportunity to mentor others—building both expertise and the next generation of AI talent. This role also provides a clear path toward leadership opportunities such as Director of AI Engineering, Head of AI Architecture, or Product Owner – AI Systems.