AI Engineer Lead

AI Engineer Lead

We are working on different areas where AI / ML can help portfolio managers, researchers, risk managers, and other functions. Some examples are: enabling traders / researchers to consume vast amounts of research and literature by organizing, summarizing information, sometimes in near real-time, doing quantitative modeling to price instruments, modeling demand and supply of commodities and other fundamentals, modeling weather & optimizing algorithmic execution of trades and modeling and building simulations of risk, to name a few.

The AI / ML work spans usage of LLMs, deep learning, reinforcement learning and other ML techniques. The work also requires building AI / ML infrastructure for data wrangling, building feature stores, building frameworks for deployments, measurements, re‑training, etc.

We are seeking an AI Engineering Lead who has experience with LLMs, deep learning, reinforcement learning, as well as an interest and ability to keep up with advancements in AI / ML. The candidate should also be strong in software engineering and be comfortable with AI / ML experimentation and productionization.

• Lead and mentor a team of AI / ML engineers
• Define technical vision and roadmap for AI / ML initiatives
• Partner with stakeholders including portfolio managers, quants, and business teams to identify high‑impact opportunities
• Architect and build scalable AI / ML solutions from experimentation to production
• Design AI / ML infrastructure including feature stores, deployment frameworks, and monitoring systems
• Establish best practices for model development, deployment, and evaluation
• Stay current with AI / ML advancements and apply them to business problems
• Drive hiring and professional development of team members

• Deep expertise in AI / ML including LLMs, deep learning, and reinforcement learning
• Strong computer science fundamentals
• Expert in Python and at least one other language (Java, C++, C#, etc.)
• Experience with cloud platforms (AWS, Azure, or Google Cloud)
• Hands‑on experience with LLM techniques: prompt engineering, fine‑tuning, PEFT, RAG
• Track record of building and deploying AI models at scale
• Experience with MLOps and production ML infrastructure

• 3+ years leading AI / ML engineering teams
• Proven ability to mentor engineers and grow talent
• Strong communication skills with technical and non‑technical stakeholders
• Experience delivering complex projects on time
• Comfortable balancing hands‑on technical work with team leadership

• Advanced degree (MS / PhD) in Computer Science, AI, ML, or related field
• Experience in financial institutions or fintech
• Background in reinforcement learning, quant modeling, or algorithmic trading
• Publications, patents, or open‑source contributions in AI / ML
• Experience building AI / ML platforms from scratch