Description

You will design and build agentic Generative AI frameworks for Capital Markets use cases, including summarization, research insights, conversational AI, and information extraction. As a hands-on technical lead, you own the architecture, model development, and implementation while guiding the team through design and code reviews. You embed LLM-based solutions into existing platforms, lead AI experimentation and hypothesis testing, and manage end-to-end MLOps including deployments, monitoring, and performance tracking. You ensure the reliability, scalability, and explainability of AI systems within regulated financial environments, collaborating closely with Quant teams and product partners.

Responsibilities

• Design and build agentic Generative AI frameworks for Capital Markets applications.
• Embed LLM-based solutions into existing Capital Markets platforms and tools.
• Lead AI experimentation, hypothesis testing, and iterative model improvement.
• Build and manage end-to-end AI Operations (MLOps) including deployments and monitoring.
• Guide team members through design reviews, code reviews, and AI best practices.

Required Skills

• 7+ years of hands-on experience building Machine Learning and Deep Learning models.
• In-depth expertise in Generative AI, Natural Language Processing (NLP), and Information Extraction.
• Strong experience with Embeddings, re-rankers, retrieval-augmented generation (RAG), and agentic frameworks.
• Proficiency in inference optimization, fine-tuning strategies, and model architectures.
• Strong understanding of Algorithms and Data Structures.
• Knowledge of distributed computing systems.
• Proven ability to act as the primary technical contributor while mentoring others.

Preferred Skills

• PhD or master’s degree in computer science, Machine Learning, or Deep Learning.
• Experience working in regulated financial environments.

Key Skills

Education

Bachelor's or Master's degrees