About Us:
Atago engineering is an Enterprise AI and Test Data Engineering consultancy and solutions provider. Our flagship platform, IntelQE, is at the forefront of revolutionizing quality engineering through cutting-edge generative AI technologies. Our platform leverages advanced AI systems to optimize testing processes, predict defects, and enhance overall software quality. Join us to shape the future of quality engineering automation.

Role Overview:
We are seeking a highly skilled and experienced AI Engineer to lead the implementation of AI systems for predictive modelling and optimization in quality engineering for our enterprise clients. The candidate will work closely with our extended engineering team. The ideal candidate will have a strong background in AI, machine learning, statistics, knowledge engineering and cloud infrastructure, with expertise in generative AI orchestration frameworks such as LangChain and LangGraph.

Key Responsibilities:

Design and develop AI systems for predictive modeling of test cases, defect detection, and test requirement optimization algorithms.

Implement and optimize generative AI solutions using frameworks like LangChain and LangGraph.

Conduct research and development on innovative AI techniques, including knowledge engineering (knowledge graphs, ontology development).

Collaborate with cross-functional teams to integrate AI models into the quality engineering automation platform.

Conduct research to stay updated on the latest advancements in AI and apply them to enhance the platform.

Develop scalable and efficient AI solutions leveraging cloud infrastructure (e.g., AWS, Azure, or Google Cloud).

Ensure the robustness, reliability, and performance of AI models in production environments.

Create and maintain comprehensive documentation for AI systems and processes.

Qualifications:

Master’s degree in Computer science, Statistics, Mathematics, or a related field.

At least 3 years of solid work experience in AI and machine learning, with a focus on predictive modelling and optimization.

Proficiency in generative AI orchestration frameworks such as LangChain, LangGraph, or similar tools.

Strong programming skills in Python and familiarity with machine learning libraries (e.g., TensorFlow, PyTorch, Hugging Face).

Experience with cloud infrastructure and deployment (AWS, Azure, Google Cloud).

Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.

Excellent problem-solving skills and the ability to work collaboratively in a team environment.

Demonstrated ability to conduct research and development in AI and knowledge engineering.

Preferred Skills:

Knowledge of advanced AI techniques, including Bayesian optimization and uncertainty estimation.

Familiarity with containerization and orchestration tools (Docker, Kubernetes)

Familiarity with MLOps practices for model lifecycle management.

· Experience with prompt engineering and fine-tuning foundation models

· Background in natural language processing and understanding

· Contributions to open-source AI projects or research publications

Why Join Us?

Be part of a dynamic team driving innovation in quality engineering automation.

Work on challenging projects with real-world impact.

Opportunities for professional growth and development.

As an enterprise AI startup on growth path, we provide immense growth and career progression opportunities, potentially employee stock options for the right candidate

Only shortlisted candidates will be contacted. You must have full working rights in Australia.