Principal AI Research Scientist

Key Responsibilities

• Monitor, evaluate, and experiment with emerging AI technologies, research breakthroughs, and industry trends, with particular emphasis on generative AI, large language models (LLMs), multimodal AI, and agentic AI systems.
• Identify opportunities to apply advanced AI techniques to complex business problems across financial services.
• Conduct original AI research and exploratory investigations to assess the feasibility and value of novel approaches.
• Develop hypotheses, design experiments, evaluate results, and communicate findings to technical and executive stakeholders.
• Contribute to publications, patents, technical whitepapers, and thought leadership initiatives where appropriate.
• Rapidly transform research concepts into working prototypes and proof-of-concepts.
• Design, develop, and validate AI solutions across the full lifecycle, from data preparation and modeling through deployment and monitoring.
• Build experimental and production-ready solutions using modern AI/ML tools, frameworks, and cloud platforms.
• Apply best practices in model evaluation, benchmarking, explainability, security, and responsible AI.

Basic Qualifications

• Bachelor's degree, or equivalent work experience
• Eight or more years of relevant experience

Preferred Skills/Experience

• Master's degree or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Applied Mathematics, Statistics, or a related technical discipline.
• Eight to ten years of experience in AI/ML research, development, and deployment.
• Strong programming skills in Python and modern AI/ML frameworks.
• Demonstrated experience designing, building, and deploying AI/ML solutions in production environments.
• Experience working across the full lifecycle of AI product development, from research and experimentation through deployment and operationalization.
• Deep expertise in machine learning, deep learning, neural networks, transformer architectures, and foundation models.
• Extensive experience with generative AI technologies, including LLMs, fine-tuning, RAG systems, model evaluation, and inference optimization.
• Experience building and evaluating agentic AI systems, multi-agent workflows, AI orchestration frameworks, and autonomous decision-making architectures.
• Strong hands-on experience with PyTorch, Hugging Face, Langchain, LangGraph, or equivalent AI ecosystems.
• Demonstrated record of innovation through publications, patents, open-source contributions, conference presentations, or significant AI solution delivery.
• Experience developing AI solutions within highly regulated industries such as financial services, healthcare, insurance, or telecommunications.
• Strong communication skills and the ability to translate complex AI concepts into actionable business outcomes.