Lead Architect for Generative AI Applications
2 weeks ago
Position: Generative AI Application Tech Lead/Architect – 01 Position
Location: New York (Hybrid Work Model)
Overview: We are in search of a skilled Generative AI Technical Lead with a robust background in Data Science and Software Engineering to spearhead the development and implementation of AI Solutions. This role involves architecting, designing, and leading a dedicated team of Generative AI Machine Learning Engineers to create a multi-agent framework. Your main focus will be on driving the development of Generative AI solutions that enhance technological capabilities, including Technology Assistants and Data Agents.
Key Responsibilities:
- Engage with cross-functional teams, including User Teams, Data Scientists, Core Development Teams, and Partner Developers, to gather requirements and guide the development and testing of AI Agents.
- Design and develop engineering solutions and generative AI applications, ensuring their scalability, efficiency, and maintainability.
- Assist in the creation of product roadmaps and define product specifications.
- Architect and design extensive enterprise-scale frameworks, such as Knowledge Graphs.
- Produce clean, high-performance, and maintainable code.
- Design and implement large-scale clustering and topic management systems.
- Utilize prompt engineering techniques to optimize and enhance large language models for improved performance and specific application needs.
- Stay updated on the latest advancements in Generative AI Application Development and actively contribute to the research and development of innovative Generative AI Applications.
Qualifications:
- A Master's or Ph.D. degree in Computer Science or a related discipline.
- At least 10 years of experience, with a minimum of 5 years focused on designing and developing ML/AI solutions.
- Demonstrated experience in a large technology startup or AI software product, leading the development and adoption of products or platforms.
- Strong proficiency in programming languages such as Java and Python, as well as ML platforms, large language models, and machine learning methodologies.
- Experience in constructing graph-based systems.
- Proven experience in architecting and leading the development of extensive Generative AI systems or platforms.
- Experience in developing technical products or platforms for large enterprises.
- Solid understanding of software engineering best practices, including version control systems (e.g., Git), code reviews, and testing methodologies.
- Familiarity with large language models (LLMs) and prompt engineering techniques; experience with vector databases is a plus.
- Excellent communication skills to effectively collaborate and present findings to both technical and non-technical stakeholders.
- Proven ability to quickly adapt and learn new technologies and frameworks.
- A proactive approach with a passion for continuous learning and research.
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