AI Engineer
Vanguard is hiring an AI Engineer. Level rates it ; you can apply on Level.
AI in this role
This role builds and supports the AI Powered Experiences team’s conversational AI orchestration platforms and shared AI infrastructure. The engineer will help deliver production-ready GenAI solutions for Workplace Technology by combining hands-on development, AI practitioner experience, and partnership with product and engineering teams. The ideal candidate has experience building and deploying AI-powered solutions, ideally including agent orchestration, conversational AI, or RAG and knowledge management systems on cloud-native infrastructure.
The role will include hands-on work across the following areas:
Agent orchestration architecture and agent-to-agent (A2A) integration patterns
Conversation history, compliance, and retention pipelines, including WORM-based patterns
Model governance and observability, including Arize and evaluation frameworks
Knowledge management and retrieval systems, including RBAC and ingestion pipelines
Model access patterns across multiple providers and model sizes
Responsibilities:
In this role, you will be expected to balance hands-on engineering delivery with architecture input, production support, stakeholder partnership, and responsible AI governance practices.
Provides system analysis, design, development, and implementation for the team’s orchestration platform, including agent registry, health check, and gatekeeper capabilities. Integrates third-party products and model observability tooling as part of scalable AI platform delivery.
Translates technical specifications into code for complex new or enhancement projects for internal clients, including conversation history and compliance pipelines, segmentation API enhancements, and agent onboarding templates. Develops, tests, and documents code artifacts, and applies software development practices that support automated testing.
Promotes code through development, test, and production environments for orchestrator services and platform infrastructure. Provides follow-up production support, submits change control requests, and maintains required documentation.
Applies software development methodology and architecture standards for agent orchestration and cloud-native services. Resolves technical issues within the engineer’s area of expertise, including performance and latency optimization.
Participates in design, code, and test inspections throughout the life cycle to identify issues. Explains technical considerations at related meetings, including those with internal clients. Performs systems analysis activities across conversation compliance, model governance, and knowledge management workstreams.
Thoroughly understands client business functions and technology needs. Has a broad understanding of Vanguard's technologies, tools, and applications, including those that interface with business area and systems.
Interfaces with cross-functional team members, and communicates systems issues at the appropriate technical level for each audience.
Thoroughly understands and complies with Information Technology and Information Security policies and procedures, and verifies that deliverables meet requirements.
Contributes to proof-of-concept, prototyping, and exploratory work that informs future AI platform capabilities.
Participates in special projects and performs other duties as assigned.
Qualifications:
Demonstrated software engineering experience in enterprise environments.
Working knowledge of cloud-native infrastructure, specifically AWS, GitHub-based development workflows, deployment pipelines
Strong programming skills in languages such as Python, JavaScript/TypeScript, or similar.
Demonstrated ability to work across technical and non-technical stakeholder groups.
Strong verbal, written, and presentation communication skills.
Minimum of five years related work experience, with at least two years of development experience.
Undergraduate degree or equivalent combination of training and experience.
Preferred Qualifications:
Experience building and delivering software or AI solutions involving agent orchestration, conversational AI, agent-to-agent or A2A protocols, RAG, knowledge management, or semantic search systems.
Exposure to multiple model providers and evaluation or observability tooling such as Arize or comparable platforms.
Experience contributing to proof-of-concept, prototyping, or exploratory AI platform work that informs future capabilities.q
Special Factors
Sponsorship
Vanguard is not offering visa sponsorship for this position.About Vanguard
At Vanguard, we don't just have a mission—we're on a mission.
To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.
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
AI Engineer at Vanguard rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● 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. Open the description and count.
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 AI engineer jobs at this level
Pay
- Typical AI engineer job
- $181k
This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs
Questions you could be asked
- 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?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: RAG and AI Safety. 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.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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