GenAI Architect - Set Sail AI

GenAI Architect - Set Sail AI

Lead the Next Generation of Generative AI-Powered Virtual Assistants

At Set Sail AI (setsail.ai), we're pioneering sophisticated virtual assistant solutions driven by cutting-edge Generative AI. We've successfully deployed over 150 AI solutions to large enterprise clients, including prominent names like MTR, BOC LIFE, CLP, Hang Seng Bank, and HK Express. We're seeking a highly skilled and passionate GenAI Architect to spearhead our Generative AI initiatives. This is a unique opportunity to lead a team, shape the future of intelligent virtual assistants, and build upon our proven track record of success.

About the Role:

As our GenAI Architect, you will be responsible for the overall direction and execution of our Generative AI strategy, focusing on building and deploying advanced LLM-powered solutions for our virtual assistant platform. You'll lead a team of talented engineers, fostering a culture of innovation and collaboration. Your deep understanding of LLMs, NLP, multimodal learning, and MLOps will be crucial to our success.

What You'll Do:

• Mentor the GenAI Team: Provide technical leadership, guidance, and mentorship to a team of AI engineers.
• Develop and Implement GenAI Strategy: Define and execute our Generative AI roadmap, aligning with business objectives.
• Research and Implement State-of-the-Art Techniques: Research, develop, and implement cutting-edge algorithms and models in LLMs, NLP, and multimodal learning, particularly in document understanding and document intelligence.
• Architect and Deploy LLM-Powered Solutions: Design and deploy robust, scalable, and efficient LLM-based solutions, leveraging best practices in software engineering and MLOps.
• Drive Innovation with RAG, LangChain, & LangSmith: Lead the exploration and implementation of advanced techniques such as Retrieval Augmented Generation (RAG), using tools like LangChain and LangSmith for optimized LLM workflows.
• Champion Multi-Agent System Design and Multimodal Learning: Explore and implement multi-agent system architectures and multimodal learning approaches to enhance the intelligence and capabilities of our virtual assistants.
• Oversee Data and Model Lifecycle: Manage the entire model lifecycle, from data preparation and cleaning to model training, hyperparameter tuning, deployment, and monitoring. Ensure data quality for effective model training.
• Collaborate & Ensure Quality: Work closely with cross-functional teams, including testing engineers, to develop and execute test cases, ensuring model accuracy and reliability. Construct and execute test cases to verify model performance.
• Build and Maintain MLOps Toolkit: Contribute to the development and maintenance of our MLOps infrastructure and toolkit to manage the machine learning lifecycle effectively.

Essential Skills & Technologies:

• Over 5 years of experience in implementing AI/ ML enterprise solutions
• Deep understanding of LLMs (e.g., GPT-4, LLaMA, QWEN) and Generative AI principles
• Expertise in Retrieval Augmented Generation (RAG) techniques
• Proficiency with LangChain and LangSmith for LLM workflow optimization
• Experience with multi-agent system design and implementation
• Familiarity with multimodal learning and representation learning
• Strong programming skills in Python
• Experience with ML frameworks (e.g., PyTorch, TensorFlow) and libraries (e.g., scikit-learn, pandas)
• Solid understanding of MLOps principles and tools
• Excellent leadership, communication, and collaboration skills