FactSet

Lead Software Engineer

In short

Lead Software Engineer role at FactSet's Funds Engineering team in Manila, building GenAI/LLM-driven, event-based automation for financial data pipelines. The role combines hands-on AI/ML engineering (LLM fine-tuning, prompt engineering, Python microservices) with technical leadership of a 10-person team. Requires 8-12 years of industry experience, including 3+ years in senior/lead roles delivering ML/AI solutions on cloud platforms (AWS/Azure/GCP), strong Python, relational databases, and mentoring experience.

About the Team
FactSet creates flexible, open data and software solutions for over 200,000 investment professionals worldwide, providing instant access to financial data and analytics that investors use to make crucial decisions.
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. The team develops & maintains an internal data collection application and manages 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.
•Lead and manage a technical team of 10 members.
•Provide technical support by incident resolution, and production troubleshooting.
•Ensure code quality through code reviews, advocating coding standards, and identifying risks before code reviews.
•Collaborate with stakeholders and the engineering team through healthy technical discussions.
•Supplement 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 relational databases (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.
•Ability to 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.
•Organized, self-directed, and resourceful with the ability to appropriately prioritize work in a fast-paced environment.
•Ability 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.
Company Overview
FactSet (NYSE:FDS | NASDAQ:FDS) helps the financial community to see more, think bigger, and work better. Our digital platform and enterprise solutions deliver financial data, analytics, and open technology to more than 8,200 global clients, including over 200,000 individual users. Clients across the buy-side and sell-side, as well as wealth managers, private equity firms, and corporations, achieve more every day with our comprehensive and connected content, flexible next-generation workflow solutions, and client-centric specialized support. As a member of the S&P 500, we are committed to sustainable growth and have been recognized among the Best Places to Work in 2023 by Glassdoor as a Glassdoor Employees' Choice Award winner.

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