{"id":1726468,"url":"https://alion.io/job/factset-lead-software-engineer","title":"Lead Software Engineer","company":{"id":2786132,"name":"Workday","domain":"myworkdayjobs-impl.com","url":"https://alion.io/company/myworkdayjobs-impl","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":99,"open_postings":62,"ghost_share":0,"stale_share":0.032,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Backend","role_family":"Backend","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Manila, Philippines"],"countries":["PH"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":19000,"max_usd":56000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1765},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Django","optional":false},{"name":"ETL/ELT","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"GCP","optional":false},{"name":"Hugging Face","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"Llama","optional":false},{"name":"MS SQL","optional":false},{"name":"MySQL","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"Transformers","optional":false},{"name":"C++","optional":true},{"name":"CI/CD","optional":true},{"name":"Databricks","optional":true},{"name":"IAM","optional":true},{"name":"pySpark","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-09-30T00:00:00Z","employer_posted_date":"2026-10-08","last_verified_at":"2026-10-18T11:57:40Z","board_verified":true,"closed_at":null,"days_open":18,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":18},"description":"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.\nAt FactSet, our values are the foundation of everything we do. They express how we act and operate, serve as a compass in our decision-making, and play a big rolein how we treat each other, our clients, and our communities. We believe that the best ideas can come from anyone, anywhere, at any time, and that curiosity is the key to anticipatingour clients’ needs and exceeding their expectations.\nYour Team's Impact\nFactSet'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.\nOver 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.\nWhat you’ll do\nDesign, fine-tune, and deploy small and open-source large language models (LLMs) such as Llama, Mistral, OpenAI GPT, etc.\nHands-on leadership in prompt engineering, few-shot prompting, and building advanced NLP/NLU workflows.\nGuide adoption of modern AI/ML frameworks (Hugging Face Transformers, LangChain, LangGraph, etc.) and architect reusable pipelines in Python.\nDrive critical systems architecture in Python, using best practices in API and microservices design (FastAPI, Flask, Django, etc.).\nProvide technical leadership to the development team, guide on architecture, design, and implementation decisions.\nShould lead and manage a technical team of 10 members.\nProvide technical support by incident resolution, and production troubleshooting\nCode quality through code reviews, advocating coding standards, and identifying risks before code reviews.\nShould collaborate with stakeholders and the healthy technical discussions engineering team.\nSupplements technical decision-making skills with broader business knowledge\nWhat We’re Looking For\n8-12 years of overall industry experience, including 3+ in senior or lead roles delivering ML/AI solutions in a cloud environment.\nBachelor’s or master’s degree in computer science or equivalent\nMastery of Python to build ETL pipelines, object-oriented patterns, code optimization, automated testing, and packaging.\nExperience with Database Relational database (MYSQL, POSTGRES, MSSQL or similar RDBMS)\nExperience on Cloud Technology AWS/Azure/GCP etc. \nHands-on deployment and scaling of AI/ML services on AWS, Azure, or GCP; proficient in containers, serverless, and infrastructure as code.\nEffectively handle multiple projects, with different agendas and projects moving forward simultaneously\nProven experience mentoring software engineers, shaping system design, and driving cross-team initiatives.\nExceptional ability to explain complex technical subjects to diverse audiences.\nExcellent organization and time management skills (Time Management)\nOrganized, self-directed, and resourceful with the ability to appropriately prioritize work in a fast-paced environment\nTo effectively mentor others in the process for developing and ensuring high quality solutions\nStrong organizational and context switching ability\nDesired Skills\nExperience in C++\nExperience with technologies like Pyspark , Databricks\nExperience with ML lifecycle tools, CI/CD pipelines, monitoring, and model governance.\nSecure cloud design, IAM, encryption, and compliance frameworks\nCompany Overview:\nFactSet (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. Learn more at www.factset.com and follow us on X and LinkedIn.\nAt FactSet, we celebrate difference of thought, experience, and perspective. 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