Salary: $120,000 - 160,000 per year Requirements:
- 10+ years of experience in software engineering, machine learning engineering, AI engineering, or a related technical discipline.
- Deep expertise designing, deploying, and supporting large-scale AI and ML systems in production.
- A record of leading complex technical initiatives from concept through deployment and ongoing operations.
- Strong knowledge of software architecture, reliability engineering, observability, MLOps, DevOps, and cloud technologies.
- Proven ability to mentor engineers and lead teams through complex technical and operational challenges.
- Experience with foundation models, large language models, and agentic AI architectures is preferred.
- Experience deploying agentic AI systems and multi-agent workflows is preferred.
- Experience with Trustworthy AI, Responsible AI, AI governance, or model risk management frameworks is preferred.
- Experience optimizing large-scale inference systems and AI infrastructure is preferred.
- Experience in highly regulated environments and mission-critical production systems is preferred.
Responsibilities: Define and lead the technical architecture for enterprise-scale AI and ML platforms, designing scalable, resilient, and reusable systems for mission-critical workloads.
Establish architectural standards, engineering patterns, and best practices for AI deployment and operations.
Guide technical decisions involving model serving, inference optimization, agent architectures, orchestration frameworks, observability, and AI infrastructure.
Partner with AI researchers to turn advanced prototypes into production-grade solutions, including capabilities in large language models, Trustworthy and Responsible AI, and agentic AI.
Create repeatable pathways from innovation to production, preserving scientific rigor while meeting enterprise engineering standards and delivering sustainable business value.
Address complex AI engineering and scalability challenges, balancing performance, latency, governance, security, and cost.
Promote MLOps, LLMOps, and AI platform engineering practices, and improve the robustness, maintainability, observability, and operational readiness of AI products.
Identify and remove architectural bottlenecks affecting scale, reliability, or client experience; raise engineering standards through coaching, architecture reviews, design guidance, and technical leadership.
Own product operational excellence, reliability, performance, and availability.
Lead responses to complex production incidents, performance degradation, model failures, and system outages, serving as the senior technical escalation point.
Establish practices for monitoring, observability, alerting, incident management, capacity planning, and service-level objectives.
Mentor engineers in troubleshooting, root-cause analysis, operational decision-making, and incident response; lead post-incident reviews and long-term corrective actions.
Develop operational processes that keep AI solutions secure, scalable, performant, and reliable for business-critical use.
Work with product, infrastructure, security, and support teams to identify operational risks and improve service reliability.
Foster a culture of technical excellence and operational ownership, and represent our team as a thought leader in scalable AI deployment, operational excellence, and responsible AI.
Technologies: Agentic AI
AI
Cloud
DevOps
Incident Management
Support
Machine Learning
MLOps
Model Serving
Security
More: We are partnering with hackajob to connect professionals with Vanguard for this Principal AI Engineer role. At Vanguard, our mission is to support our clients long-term financial wellbeing and transform their lives through our products and services. Were committed to learning and developing as individuals and as a team, with our mission guiding us from Malvern to Melbourne. Youll work at the forefront of applied AI with world-class researchers and leaders across research, product, and engineering, helping turn advanced research into meaningful outcomes for clients while tackling significant AI engineering and operational challenges. Vanguards hybrid working model combines flexibility with in-person learning, collaboration, and connection. We are not offering visa sponsorship for this position.
last updated 40 week of 2026
