GenAI Tech Lead

Generative AI Tech Lead

Project Description

The engineer is supposed to participate in pre-sales, discovery phases of projects and lead projects. They are also expected to be capable of starting the project from scratch and lead the team.

Details on Tech Stack

• Python
• Prompt engineering
• Best practices for prompt engineering
• How LLM can be used in applications for a variety of tasks
• NLP
• Understanding of typical NLP problems: classification, NER, summarization, question answering, sentiment analysis, etc.
• Theoretical intuitive understanding of how Transformers work (tokenization, attention, etc).
• Word and sentence embeddings
• Vector search
• Vector databases, performance tuning
• Document chunking techniques
• LLM applications development
• LangChain, LlamaIndex
• Chain of Thoughts, DSP, and other techniques
• Agents and tools
• Google cloud (GCP)

Nice to Have Requirements

• Preferable, the engineers are expected to have IT services/consulting experience.
• Proficient in developing LLM-powered systems using advanced prompt engineering techniques, RAG and agentic design patterns. Experienced with frameworks like LangChain, LlamaIndex, and DSPy.
• Familiar with evaluation approaches and metrics for different types of LLM-based systems.
• Experienced with keyword and vector search methods, including understanding of their underlying algorithms. Familiar with popular vector search engines.
• Competent in various document understanding models and techniques to parse complex documents and implement effective chunking strategies for RAG systems.
• Familiar with LLM and embedding models fine-tuning techniques.
• Competent in using joint vision-language and generative models to solve various problems related to image generation, visual question answering, and multi-modal search. Familiar with diffusion models and associated techniques like LoRA, Dreambooth, and ControlNet.
• Understanding of the challenges and risks associated with the development of Generative AI systems and how to mitigate them.
• Familiar with various architecture design patterns for different types of LLM-based applications such as chatbots, text2sql, document understanding, etc. Familiar with various approaches to scalability and cost reduction in Generative AI systems.
• Ability to stay updated with the latest advancements in Generative AI and integrate emerging technologies to drive innovation and improve the performance of AI systems.
• Familiar with Responsible AI principles and Human-AI interaction design best practices.

Perks & Benefits:

• Competitive salary & performance-based bonuses
• Remote work flexibility / Hybrid options
• Continuous learning budget & GenAI certifications
• Opportunity to work on cutting-edge AI projects
• Dynamic and collaborative team environment