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GenAI Application Tech Lead or Arch
1 month ago
Responsibilities:
- Collaborate with cross-functional teams such as User Teams, Data Scientists, Core Development Team and Partner Team Developers to identify requirements and architect and lead the development and testing of the AI Agents.
- Design and develop Engineering Solutions & generative AI Applications for above ensuring scalability, efficiency, and maintainability of such solutions.
- Assit for Product Roadmap creation & define product requirements.
- Architect and Design a large enterprise scale framework such as Knowledge Graph.
- Write clean, high-performance, high-quality, maintainable code.
- Design & Implement large scale Clustering, Topic Management system.
- Implement prompt engineering techniques to fine-tune and enhance LLMs for better performance and application-specific needs.
- Stay abreast of the latest advancements in the field of Generative AI Application Development and actively contribute to the research and development of new Generative AI Applications.
Requirements:
- A Master's or Ph.D. degree in Computer Science or a related field.
- Minimum 10 years experience with atleast 5 years in designing and building ML/AI Solutions.
- Proven experience working in a large Technology Startup or AI Software Product leading development and adoption of the product or a platform.
- Strong proficiency in programming languages such as Java, Python, ML Platorms, LLMs, Machine Learning etc
- Experience in building Graph based systems.
- Experience architecting & leading development of large Generative AI system or platform.
- Experience in development of technical product or platform for large enterprises.
- Solid knowledge of software engineering best practices, including version control systems (e.g., Git), code reviews, and testing methodologies.
- Experience with large language models (LLMs) & prompt engineering techniques, vector DB's ( Nice to have )
- Strong communication skills to effectively collaborate and present findings to both technical and non-technical stakeholders.
- Proven ability to adapt and learn new technologies and frameworks quickly.
- A proactive mindset with a passion for continuous learning and research.