Senior AI Systems Engineer – Production-Grade LLM/RAG

Visa Hunt; Australia; On-site; AUD 244,000 - 279,000; Full time

Job summary

Iovance Biotherapeutics seeks a senior AI engineer to lead hands-on design, build, and deployment of production AI systems. You will own architecture, retrieval pipelines, prompts, and evaluation for high-accuracy use cases across manufacturing, quality, regulatory, and IT security in a regulated life sciences setting.

You will implement RAG on AWS (S3, Redshift, Bedrock), manage embeddings, vector stores, grounding, and citations, while ensuring security, traceability, and compliance.

Qualifications

• 10+ years in software/AI/ML with the latest 1+ years on LLM apps.
• Hands-on RAG with embeddings, vector stores, grounding.
• Experience with multiple frontier models and task fit.
• Strong Python, cloud AWS, and MLOps knowledge.
• Ability to ship production AI in regulated life sciences.

Responsibilities

• Design, build, and ship AI systems following the roadmap.
• Implement production-grade RAG on AWS infrastructure.
• Create evaluation harnesses with metrics and tests.
• Integrate AI with enterprise systems using MCP and APIs.
• Own LLM security controls and prompt safety measures.
• Develop AI agents for regulated environments with oversight.
• Establish modern engineering practices and reproducible builds.
• Evaluate AI vendors and provide concise recommendations.
• Operate audit logging, access control, model changes.
• Produce architecture diagrams, data flow, and validation docs.
• Mentor junior engineers and stay current with AI tooling.

Skills

LLM development

RAG systems

AWS

Python

CI/CD

Security controls

Mentoring

Education

Bachelor's or higher in CS/Engineering

Tools

Bedrock

S3

Redshift

OpenSearch

Git

Job description

Iovance Biotherapeutics seeks a senior AI engineer to lead hands-on design, build, and deployment of production AI systems. You will own architecture, retrieval pipelines, prompts, and evaluation for high-accuracy use cases across manufacturing, quality, regulatory, and IT security in a regulated life sciences setting.

You will implement RAG on AWS (S3, Redshift, Bedrock), manage embeddings, vector stores, grounding, and citations, while ensuring security, traceability, and compliance.