Lead Software Engineer – GenAI, LLM, Python & Cloud AI

Your Team's Impact FactSet's Funds Engineering team under DSE is focused on delivering Funds data (e.g., fund expense ratio, daily price & info data) coming from different sources by providing database solutions and automated processes which follow an Extract-Transform-Load (ETL) procedure. We develop & maintain an internal data collection application and manage funds data distribution services, routinely increasing efficiency year over year through automation. Over time, the team has developed a robust and high-performing data pipeline capable of generating best in-class structured datasets that power FactSet’s products. Currently, the team is advancing this ecosystem by driving end-to-end automation across multiple stages of the pipeline. This includes the development of an event-driven, GenAI-centric, agent-based infrastructure aimed at enhancing efficiency, scalability, and innovation in data processing workflows. What you’ll do Design, fine-tune, and deploy small and open-source large language models (LLMs) such as Llama, Mistral, OpenAI GPT, etc. Hands-on leadership in prompt engineering, few-shot prompting, and building advanced NLP/NLU workflows. Guide adoption of modern AI/ML frameworks (Hugging Face Transformers, LangChain, LangGraph, etc.) and architect reusable pipelines in Python. Drive critical systems architecture in Python, using best practices in API and microservices design (FastAPI, Flask, Django, etc.). Provide technical leadership to the development team, guide on architecture, design, and implementation decisions. Should lead and manage a technical team of 10 members. Provide technical support by incident resolution, and production troubleshooting Code quality through code reviews, advocating coding standards, and identifying risks before code reviews. Should collaborate with stakeholders and the healthy technical discussions engineering team. Supplements technical decision-making skills with broader business knowledge What We’re Looking For 8-12 years of overall industry experience, including 3+ in senior or lead roles delivering ML/AI solutions in a cloud environment. Bachelor’s or master’s degree in computer science or equivalent Mastery of Python to build ETL pipelines, object-oriented patterns, code optimization, automated testing, and packaging. Experience with Database Relational database (MYSQL, POSTGRES, MSSQL or similar RDBMS) Experience on Cloud Technology AWS/Azure/GCP etc. Hands-on deployment and scaling of AI/ML services on AWS, Azure, or GCP; proficient in containers, serverless, and infrastructure as code. Effectively handle multiple projects, with different agendas and projects moving forward simultaneously Proven experience mentoring software engineers, shaping system design, and driving cross-team initiatives. Exceptional ability to explain complex technical subjects to diverse audiences. Excellent organization and time management skills (Time Management) Organized, self-directed, and resourceful with the ability to appropriately prioritize work in a fast-paced environment To effectively mentor others in the process for developing and ensuring high quality solutions Strong organizational and context switching ability Desired Skills Experience in C++ Experience with technologies like Pyspark , Databricks Experience with ML lifecycle tools, CI/CD pipelines, monitoring, and model governance. Secure cloud design, IAM, encryption, and compliance frameworks