The Global Investment & Finance Systems (GIFS) Lead Forward Deployed Engineer (FDE) is a senior individual contributor who partners directly with the business while remaining accountable to IT priorities, engineering standards, and governance. Working alongside investment professionals and quantitative researchers, the Lead FDE identifies high-value opportunities and personally architects, builds, and validates solutions from experimentation through the appropriate GIFS SDLC pathway.
Based in GIFS UK, the role partners across Vanguard's Investment Management Group (IMG), including the Investment Strategy Group (ISG), using rapid, hands-on iteration to explore quantitative and analytical challenges, test potential solutions, and determine which opportunities warrant further investment and productionalization.
The Lead FDE also sets technical direction, mentors engineers, advises IMG and GIFS leaders, and turns direct delivery experience into reusable capabilities and engineering practices for the broader organization.
KEY RESPONSIBILITIES:
- Partner closely across all teams within the UK Investment Management Group to understand complex workflows and rapidly shape, test, and prioritize high-value quantitative and analytical opportunities.
- Translate ambiguous investment challenges into actionable technical opportunities, selecting the right approach across software, data, AI, machine learning, optimization, and human judgment.
- Personally architect, build, and validate solutions from rapid experimentation through MVP and initial production deployment.
- Lead the productionalisation of research code, quantitative models, analytical tools, and high- or critical-risk EUCTs, strengthening testing, reproducibility, performance, data lineage, and operational support.
- Establish scalable engineering patterns for AI-enabled solutions, including human-in-the-loop controls, reusable components, and evaluation methods addressing quality, safety, latency, cost, and readiness.
- Exercise senior technical judgment with Product, Engineering, Architecture, Platform, Security, and enterprise governance teams on whether capabilities should be refined, elevated, transitioned, reused, or retired.
- Lead through hands-on delivery by setting technical direction, developing critical components, mentoring engineers, and resolving complex delivery barriers.
- Translate successful UK engagements into reusable code, evaluation methods, and engineering patterns, working with Innovation and Emerging Technology to bring emerging capabilities into local delivery and share lessons across GIFS.
WHAT YOU BRING TO THE ROLE (COMPETENCIES):
- Strong understanding of investment management, portfolio, trading, and quantitative research workflows, with the judgment to turn ambiguous problems into actionable technical opportunities.
- Deep software and data engineering expertise, with a record of personally delivering reliable, maintainable, well-documented production solutions using modern testing, CI/CD, logging, and source-control practices.
- Strong quantitative grounding in mathematics, statistics, numerical methods, or a related discipline, with the ability to work effectively alongside quantitative researchers and distinguish research questions from implementation decisions.
- Hands-on expertise across Python, data engineering, cloud platforms, AI and machine learning, optimization, and modern application development.
- Experience architecting AI-enabled and agentic solutions, including RAG, tool use, human-in-the-loop controls, and evaluation frameworks.
- Ability to understand and modernize logic embedded in Excel, Access, VBA, SQL, Tableau, and other EUCT solutions while preserving essential business and quantitative logic.
- Strong enterprise delivery judgment across architecture, security, privacy, controls, auditability, data governance, evaluation, and operational readiness.
- Ability to influence senior business and technology leaders, communicate tradeoffs clearly, and guide decisions on investment, adoption, reuse, and retirement.
- Ability to lead through hands-on delivery across distributed teams and global locations while maintaining accountability for technical quality and business outcomes.
Qualifications- Bachelor's degree in computer science, engineering, mathematics, statistics, physics, or a related quantitative or technical field, or equivalent experience.
- 10+ years of relevant software, data, quantitative, or analytics engineering experience.
- Demonstrated experience leading technical workstreams and delivering production-quality solutions across teams or business areas.
- Experience supporting investment management, quantitative research, or related front-office analytical functions.
- Financial services experience and experience with cloud-based data or AI platforms preferred.
How We WorkVanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.
