AI Engineer with Master's Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field (Mandatory). The role is Sydney based.Simplyai is seeking a highly motivated AI Engineer to join our growing Data & AI practice. The successful candidate will work on enterprise-grade AI, Generative AI, Machine Learning, and Intelligent Automation solutions for leading organizations across Australia.

This role requires strong software engineering fundamentals combined with practical experience in machine learning, cloud-native application development, APIs, and modern AI frameworks. The ideal candidate should be comfortable building production-ready AI systems rather than only developing machine learning models.

Key Responsibilities

• Design, develop, and deploy AI-powered applications and services.

• Build and maintain Generative AI solutions using Large Language Models (LLMs).

• Develop Retrieval-Augmented Generation (RAG) systems using vector databases and enterprise knowledge sources.

• Create scalable backend services and APIs to support AI applications.

• Build data ingestion, transformation, and feature engineering pipelines.

• Fine-tune, evaluate, and optimize machine learning and foundation models.

• Integrate AI solutions with enterprise systems, databases, and cloud platforms.

• Collaborate with solution architects, data scientists, and business stakeholders to deliver AI outcomes.

• Monitor and improve model performance, reliability, security, and scalability.

• Contribute to AI governance, responsible AI, and best-practice engineering standards.

Required Skills

Programming & Software Engineering

• Strong proficiency in Python.

• Good understanding of Java or TypeScript.

• Experience building REST APIs and microservices.

• Strong understanding of software engineering principles and design patterns.

AI & Machine Learning

• Experience developing machine learning solutions using Scikit-learn, XGBoost, PyTorch, TensorFlow, or similar frameworks.

• Understanding of model training, evaluation, feature engineering, and deployment.

• Exposure to Generative AI, LLMs, prompt engineering, and AI agents.

• Understanding of RAG architectures and vector databases.

Data Engineering

• Experience working with structured and unstructured datasets.

• Knowledge of SQL and data transformation pipelines.

• Familiarity with PostgreSQL, MySQL, SQL Server, MongoDB, or similar databases.

Cloud & DevOps

• Experience with AWS, Azure, or Google Cloud.

• Knowledge of Docker and containerized deployments.

• Familiarity with CI/CD pipelines and Infrastructure as Code.

• Understanding of Kubernetes is desirable.

Distributed Systems

• Understanding of event-driven architectures.

• Experience with Kafka, Redis, message queues, or asynchronous processing frameworks.

• Knowledge of scalable, distributed backend systems.

Preferred Skills

• Experience with Azure OpenAI, OpenAI, Anthropic Claude, Gemini, or similar LLM platforms.

• Experience with LangChain, LlamaIndex, CrewAI, AutoGen, Semantic Kernel, or similar frameworks.

• Exposure to MLOps and AI deployment pipelines.

• Experience implementing AI solutions in enterprise environments.

• Knowledge of observability tools such as Grafana, Prometheus, and centralized logging platforms.

Personal Attributes

• Strong analytical and problem-solving skills.

• Passion for Artificial Intelligence and emerging technologies.

• Excellent communication and stakeholder engagement skills.

• Ability to work independently and collaboratively in a fast-paced environment.

• Strong attention to detail and commitment to delivering quality solutions.