Lead AIML Engineer

Responsibilities

• Architect build and deploy RAG pipelines including chunking embeddings vector stores retrieval ranking grounding and evaluation.

• Design and implement Graph RAG solutions leveraging knowledge graphs for multihop reasoning and structured retrieval.

• Build robust scalable ML/LLM services using Python (and Java where applicable) with welldesigned APIs and microservices.

• Develop data processing pipelines for ingestion transformation metadata extraction and indexing.

• Implement observability monitoring evaluation harnesses automated testing and CI/CD for GenAI services.

• Optimize retrieval quality response accuracy latency and cost across model retrieval layers.

• Apply responsible AI security and governance practices for LLM systems (e.g. content filtering guardrails model monitoring).

• Collaborate with product data engineering and cloud platform teams to translate business problems into robust AI solutions.

• Produce clear documentation design specs and operational runbooks for all delivered components.

Required Qualifications

• 3 years of experience as an ML Engineer AI Engineer or similar role.

• Handson experience building GenAI applications and RAG systems endtoend.

• Strong proficiency in Python for ML/LLM development.

• Experience with vector databases (e.g. pgvector Pinecone Weaviate FAISS) and embedding models.

• Knowledge of LLM frameworks (LangChain LlamaIndex Transformers etc.).

• Strong understanding of cloud environments (AWS/Azure) and containerized deployments.

• Solid software engineering foundations APIs microservices version control testing CI/CD.

• Experience with data pipelines ETL/ELT and processing unstructured data.

• Ability to evaluate retrieval quality implement ranking strategies and build evaluation datasets.

• Excellent communication skills and ability to work in crossfunctional teams.

Preferred Qualifications

• Graph RAG experience using knowledge graphs graph databases or graphbased retrieval.

• Experience with Java for backend services data processing or connector development.

• Familiarity with MLOps/LLMOps tooling and practices.

• Experience integrating AI outputs into metadata/catalog systems or workflows.

• Experience with prompt engineering guardrailing and LLM safety controls.

What Were Looking For

A builder who loves engineering elegant reliable systems that scale someone who understands both machine learning and strong software engineering practices is passionate about GenAI and is excited to push the boundaries of RAG and Graph RAG capabilities.

Special Factors

Sponsorship

About Vanguard

At Vanguard we dont just have a missionwere 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.