Lead Architect for Generative AI Applications
2 weeks ago
Position: Generative AI Application Tech Lead/Architect – 01 Opening
Location: New York (Hybrid Work Model)
Overview: We are looking for a skilled Generative AI Technical Lead with a robust background in Data Science and Software Engineering to spearhead the creation and implementation of AI Solutions. In this pivotal role, you will be instrumental in architecting, designing, and guiding a dedicated team of Generative AI Machine Learning Engineers to develop a multi-agent framework. Your main focus will be on leading the development of Generative AI solutions aimed at enhancing technological advancements such as Technology Assistants and Data Agents.
Key Responsibilities:
- Collaborate with interdisciplinary teams, including User Teams, Data Scientists, Core Development Teams, and Partner Developers, to ascertain requirements and oversee the development and evaluation of AI Agents.
- Design and implement engineering solutions and generative AI applications, ensuring they are scalable, efficient, and maintainable.
- Assist in the formulation of the Product Roadmap and define product specifications.
- Architect and design large-scale enterprise frameworks, such as Knowledge Graphs.
- Produce clean, high-performance, and maintainable code.
- Design and implement extensive 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 developments in Generative AI Application Development and actively engage in the research and development of innovative Generative AI Applications.
Qualifications:
- A Master's or Ph.D. in Computer Science or a related discipline.
- At least 10 years of experience, with a minimum of 5 years dedicated to 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 expertise in programming languages such as Java, Python, and familiarity with ML Platforms, LLMs, and Machine Learning.
- Experience in constructing graph-based systems.
- Proven track record 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 insights to both technical and non-technical stakeholders.
- Proven ability to quickly adapt and learn new technologies and frameworks.
- A proactive approach with a commitment to continuous learning and research.
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