Vulcan Labs ★ 4.3

Job Purpose

In this role, you will work at the forefront of artificial intelligence, focusing on building and enhancing solutions using Generative AI techniques. Your primary responsibilities will include developing Retrieval-Augmented Generation (RAG) systems, extracting insights from large datasets, and integrating AI capabilities into enterprise workflows. You will collaborate with cross-functional teams to deliver scalable AI solutions that transform business processes and generate actionable insights.

Key Accountabilities (1)
AI Development

• Design and implement Retrieval-Augmented Generation (RAG) systems to improve document search, summarization, and knowledge retrieval.
• Fine-tune and deploy large language models (LLMs) for specific use cases, ensuring high performance and accuracy.
• Develop APIs for seamless integration of generative AI solutions into existing platforms.
  
  

Key Accountabilities (2)
Data Insights & Analytics

• Analyze large, complex datasets to uncover patterns and actionable insights using AI-powered tools.
• Build predictive models and algorithms to support data-driven decision-making.
• Collaborate with stakeholders to translate business challenges into AI solutions.
  
  

Key Accountabilities (3)
Solution Deployment

• Collaborate with engineering teams to ensure robust deployment of AI models in production environments.
• Optimize AI systems for scalability, performance, and cost-efficiency.
• Monitor and maintain AI models, addressing issues related to accuracy, drift, and user feedback.
  
  

Key Accountabilities (4)
Collaboration & Innovation

• Work closely with data scientists, software engineers, and domain experts to design and implement cutting-edge AI solutions.
• Stay updated on the latest advancements in generative AI and LLM technologies, recommending innovative approaches.
• Contribute to knowledge-sharing sessions and team growth in AI best practices.
  
  

Key Relationships - Direct Reports

Key Relationships - Internal Stakeholders
Teams within the Transformation Office and relevant departments in the Bank

Key Relationships - External Stakeholders
Partners providing professional services

Success Profile - Qualification and Experiences

• Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field. PhD preferred.
• Proven experience with large language models (e.g., GPT, LLaMA) and related frameworks (e.g., Hugging Face, LangChain).
• Strong proficiency in Python and relevant libraries (e.g., PyTorch, TensorFlow).
• Hands-on experience with Retrieval-Augmented Generation (RAG) techniques.
• Expertise in natural language processing (NLP), deep learning, and data analytics.
• Familiarity with cloud platforms (e.g., AWS, Databricks) and containerization tools (e.g., Docker, Kubernetes).
• Excellent problem-solving and communication skills, with the ability to work collaboratively in a team environment.
  
  

Preferred Skills

• Experience with vector databases for knowledge retrieval.
• Knowledge of MLOps tools and best practices.
• Background in business intelligence or working with financial, banking, or enterprise datasets.
• Familiarity with building and deploying chatbot solutions and integrating them with APIs.