Lead Forward Deployed Engineer
Vanguard is hiring a Lead Forward Deployed Engineer in Melbourne, Australia. Level rates it ; you can apply on Vanguard.
Level's read on this job
- On Level's scale, this forward deployed engineer role is Little AI ●○○○: aI is not part of the work.
- Tools and skills the posting cites include prompt engineering, RAG and AI safety.
- Level classifies it as a lead role.
- Level lists 335 other open roles at Vanguard.
- The role was posted within the past two weeks.
AI in this role
Lead forward-deployed engineer embedding with investment management and finance teams to build production solutions.
About Vanguard
50 years ago, John C. Bogle had a vision to start an investment company that did things differently. A company with no external shareholders. Where all the profits were invested back into the business and used to lower costs. Evidently, it was as bold as it was brilliant. To this day, Vanguard Group still has no external shareholders. That means no share prices to protect, and no profits to generate for outside owners.
Today, Vanguard is one of the world’s largest investment management companies, serving more than 50 million investors worldwide. For more than 30 years Vanguard Australia has been supporting individual investors, financial advisers, and superannuation members to achieve their long-term financial goals.
Team & Opportunity
The Global Investment & Finance Systems (GIFS) Lead Forward Deployed Engineer (FDE) is a senior individual contributor who embeds directly with partners in Vanguard’s Investment Management Group (IMG) and Finance division to turn complex ideas and emerging opportunities into governed, production-quality solutions. Lead FDEs work alongside portfolio managers, traders, analysts, and finance professionals to understand their workflows, shape and prioritize high-value opportunities, and personally architect, build, and validate solutions. They exercise senior technical and business judgment across business value, technical feasibility, risk, and operational readiness, guiding successful capabilities from experimentation through the appropriate software development lifecycle process.
This role will align with Vanguard’s international business, supporting quantitative research across asset classes, portfolio management, and trading capabilities across regions. The Lead FDE will remain deeply engaged in hands-on delivery while setting technical direction, mentoring other engineers, advising international business and GIFS leaders, and translating direct delivery experience into reusable patterns and capabilities for the broader organization.
Core Responsibilities
- Embed directly with researchers, portfolio managers, and traders across Vanguard’s international business to understand complex workflows, surface high-value opportunities from each region, and own their prioritization through a shared global backlog in close consultation with GIFS and Investment Management leaders, aligning FDE capacity to measurable investment and operational outcomes.
- Serve as a senior technical partner to international business and GIFS leaders, applying domain and engineering judgment to determine when AI, machine learning, optimization, deterministic development, or human judgment is the appropriate response to a business problem.
- Personally architect, build, and validate AI-enabled applications, automations, and redesigned workflows, leading complex solutions from early experimentation through MVP and limited production.
- Shape and lead the systematic replacement of high-risk and critical-risk Excel, Access, Tableau, and other EUCT solutions across investment and supporting functions, migrating valuable logic and data into governed, supportable environments via an SDLC process.
- Establish scalable engineering patterns for AI-enabled solutions, including agent workflows, human-in-the-loop controls, reusable components, and evaluation methods addressing quality, safety, latency, cost, and operational readiness.
- Exercise senior technical judgment over solution maturity, partnering with Product, Engineering, Architecture, Platform, Security, and Risk teams to recommend whether capabilities should be refined, elevated, transitioned, reused, or retired.
- Modernize workflows and decision-support processes across multiple investment domains and functions by reducing manual effort, strengthening data quality and governance, and enabling improved insights, faster decisions, and more efficient execution.
- Lead through hands-on delivery by setting technical direction, developing critical solution components, mentoring other engineers, and resolving complex technical or delivery barriers across related engagements.
- Translate successful international engagements into reusable code, templates, evaluation methods, reference patterns, and implementation guidance that strengthen future FDE delivery across regions and the broader GIFS organization.
- Partner with international business and GIFS leadership to communicate delivery status and realized value, identify broader deployment opportunities, and shape the continued evolution of Vanguard’s engineering practices and responsible AI adoption.
WHAT YOU BRING TO THE ROLE (COMPETENCIES):
- Deep software and data engineering expertise, with a record of personally building reliable, maintainable, well-documented production solutions using modern testing, CI/CD, logging, versioning, and source-control practices.
- Hands-on expertise architecting and deploying AI-enabled and agentic solutions, including prompt engineering, RAG, tool-use patterns, human-in-the-loop controls, and evaluation frameworks.
- Strong technical breadth across AI, machine learning, optimization, data engineering, and deterministic software development, with the judgment to select the appropriate approach for each problem.
- Experience with cloud-based data and AI platforms and the ability to integrate emerging capabilities into secure, scalable enterprise environments.
- Advanced proficiency in Python and modern application and data tooling, including the ability to understand and modernize logic embedded in Excel, Access, VBA, SQL, Tableau, and other EUCT solutions.
- Strong command of AI and solution evaluation practices, including quality, safety, latency, cost, monitoring, version management, operational readiness, and appropriate human oversight.
- Demonstrated ability to personally architect and build complex solutions while setting technical direction, mentoring engineers, and improving quality through direct design and code review.
- Strong enterprise delivery judgment, balancing rapid experimentation with architecture, security, privacy, risk, auditability, data governance, and SDLC expectations.
- Ability to develop deep domain fluency, challenge ambiguous problem framing, and translate investment and business workflows into actionable technical opportunities.
- Demonstrated ability to influence senior business and technology leaders, clearly communicate technical tradeoffs, and guide decisions on investment, adoption, elevation, reuse, and retirement.
- Experience creating reusable engineering patterns, evaluation methods, and implementation guidance that extend beyond a single engagement or team.
- Ability to lead through hands-on delivery across distributed teams and global time zones (US, UK, India, Australia), maintaining clear accountability for technical quality and business outcomes and consistent, transparent communication with stakeholders in every region.
QUALIFICATIONS:
- Bachelor's degree in Computer Science, Data Science, Engineering, or related technical field, or equivalent combination of training and experience.
- Minimum of 7+ years of related work experience in software engineering, data engineering, data science, or analytics engineering.
- Demonstrated experience leading technical workstreams and delivering production-quality solutions across multiple teams or business areas.
- 2+ years building and deploying GenAI/LLM-powered solutions in client or production environments preferred.
- 5+ years with cloud-based AI & Data platforms/products.
- Deep financial services domain knowledge highly preferred
Inclusion Statement
Vanguard’s continued commitment to diversity and inclusion is firmly rooted in our culture. Every decision we make to best serve our clients, crew (internally employees are referred to as crew), and communities is guided by one simple statement: “Do the right thing.”
We believe that a critical aspect of doing the right thing requires building diverse, inclusive, and highly effective teams of individuals who are as unique as the clients they serve. We empower our crew to contribute their distinct strengths to achieving Vanguard’s core purpose through our values.
When all crew members feel valued and included, our ability to collaborate and innovate is amplified, and we are united in delivering on Vanguard’s core purpose.
Vanguard Australia is proud to hold the Employer of Choice for Gender Equality (EOCGE) citation, awarded by WGEA, recognising our strong commitment to gender equality and our dedication to inclusive policies, gender balanced outcomes and a safe, respectful workplace.
Our core purpose: To take a stand for all investors, to treat them fairly, and to give them the best chance for investment success.
How We Work
Vanguard 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.
How we rate this
Lead Forward Deployed Engineer at Vanguard rates 0 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in forward deployed engineer jobs at this level
Pay
- Typical forward deployed engineer job
- $180k
This posting doesn't list pay. Use the typical forward deployed engineer figure when pay comes up. See forward deployed engineer jobs
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you think about the risk of an AI system in this kind of role failing silently?
- Tell me about a project where software engineering was part of your work. What did you do?
- Tell me about a project where quantitative research was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Prompt engineering, RAG, AI Safety, Software Engineering, and Quantitative Research. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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