AI Full Stack Engineer

Accelerate the possible by joining a winning Amcor team that’s transforming the packaging industry and improving lives around the world.

At Amcor, we unpack possibility through our innovative and responsible packaging to provide solutions that benefit our customers, our people and our planet. More than 10,000 consumers worldwide encounter our products every second and rely on us for safe access to food, medicine and other goods. We value their trust by making safety our guiding principle. It’s our core value and integral to how we do business.

Beyond this core principle, our shared values and behaviors unite us as we work together to elevate customers, shape lives and protect the future. We champion our customers and help them succeed. We play to win – adapting quickly in an ever changing world – and make smart choices to safeguard our business, our communities and the people we serve for generations to come.

And we invest in our world-class team, empowering our colleagues to unpack their potential, because we believe when our people grow, so does our business.

To learn more about playing for Team Amcor, visit  I Linked In I Glassdoor I Facebook I You Tube Job  Description About the role

An AI Full Stack Engineer is responsible for designing, developing, and deploying machine learning, AI models and algorithms to enhance products and services, collaborates with key business data owners, data governance, data engineering, and IT application business analysts to align strategies, maintain execution transparency, and support effective delivery.

This role leads the design and execution of regional or multi-site AI/ Gen AI/ML Models that drive operational efficiency, sustainability, and supply chain visibility. Defines and manages AI/ML roadmaps within a business domain, manages cross-functional teams, and translates business needs into scalable data solutions. Operates with moderate autonomy, influences data architecture decisions, and ensures alignment with global standards. Skilled in cloud platforms, data modelling, and stakeholder engagement.

In addition to AI/ML expertise, this role encompasses full stack development — building and maintaining frontend user interfaces, RESTful and Graph

QL APIs, backend services, and database layers — to deliver end-to-end AI-powered applications from model to production UI.Key Job Accountabilities Model Development:
Design and develop machine learning models and algorithms tailored to specific business needs. Design and implement production‑ready RAG systems that connect LLMs to enterprise data sources (data lake, Microsoft Fabric, SAP, MES, document repositories); own prompt templates, retrieval strategies, and evaluation; optimize for accuracy, latency, and cost. Build AI agents that orchestrate multi‑step workflows

Collaboration:

Work closely with data scientists, software engineers, and cross-functional teams to integrate models into production systems.

Data Analysis:
Analyze large and complex datasets to extract actionable insights and improve model performance.

Optimization:
Tune and enhance model performance and accuracy through iterative testing and validation."Documentation:
Maintain thorough documentation of AI/ML models, experiments, and processes to ensure reproducibility and knowledge sharing.

Stay Updated:
Keep abreast of the latest advancements in AI and ML technologies to apply innovative solutions in projects.

Establish and maintain working relationships with Amcor business stakeholders. Engage enterprise decision makers and stakeholders to facilitate group decisions and outcomes.

Full Stack Development:
Design and build end-to-end AI-powered applications encompassing frontend user interfaces, backend APIs, and integration layers that surface AI/ML model outputs to end users.

API & Backend Services:
Develop and maintain RESTful and/or Graph

QL APIs and backend microservices that connect AI/ML models to enterprise data sources and front-end applications.

Database Design & Management:
Design, implement, and optimize relational and No

SQL database schemas to support AI application data needs, including vector databases for embedding storage and retrieval.

Clo…