AI Engineer

*Temus is a Temasek-backed consulting firm providing digital transformation solutions for the private and public sectors. W**e aspire to be a strategic partner in realising the Singapore Government’s Smart Nation vision. We are headquartered in Singapore and have more than 400 employees across a wide range of disciplines in strategy, design, architecture, technology, data & AI.* **Your Role** - Harness your expertise in AI engineering, delivery, and governance to solve complex problems and deliver transformative change for clients and citizens. - Make an outstanding contribution to a world-class AI and data team. - Develop and maintain relationships with a broad range of clients, colleagues, and partners across a variety of contexts and formats. - Invest continuously in building and extending your knowledge and skills. **Your Background** - At least 3 years of relevant working experience in fields related to artificial intelligence, machine learning, data science, or software engineering. - Completed at least one hands-on AI development and deployment end-to-end. - Exposure to agentic AI concepts such as multi-agent systems, tool-use, RAG pipelines, or autonomous task execution is highly desirable. - At least 3 years of implementation experience with serverless computing, CI/CD, containerisation, Infrastructure as Code, code version control and automated testing. - Exposure to one or more cloud services: AWS, Azure or GCP. - Candidates should demonstrate strength in either AI Engineering or ML Engineering (see below). Strength in both is a plus. AI Engineering (LLM & Agentic Systems) - Practical hands-on experience with LLMs and agentic tooling: LangChain, LangGraph, AutoGen, CrewAI, OpenAI API, Anthropic API, AWS Bedrock, Google Vertex AI, Azure ML, Hugging Face Transformers, MLFlow, Dataiku, MS Fairlearn, Google PAIR. - Experience with prompt engineering, fine-tuning, and responsible AI evaluation. ML Engineering / MLOps - Practical hands-on experience with ML development and deployment tooling: Jupyter, PyTorch, TensorFlow, Scikit-learn, AWS SageMaker, MLFlow, Docker, Kubernetes, Terraform, Ansible, Datadog. - Broad knowledge of NLP, computer vision, recommendation systems, reinforcement learning and time series forecasting. - Exposure to model experiment tracking and training workflows: hyperparameter tuning, experiment logging (e.g. MLFlow, Weights & Biases), and reproducible training runs. - Exposure to the MLOps lifecycle: data versioning, model training pipelines, experiment tracking, model registry, deployment, monitoring, and retraining triggers — using tools such as MLFlow, Weights & Biases, Kubeflow, AWS SageMaker Pipelines, Azure ML Pipelines, or Google Vertex AI Pipelines. *Temus is an equal opportunities employer. We welcome applications from all. We do not discriminate by race, religion, belief, ethnicity, origin, disability, age, partnership status, sexual orientation, or gender identity.* *We see the diversity of our team as a strategic advantage, and we work actively to maintain it.* *By applying for this role, you have read and acknowledge the data privacy statement via this link - [](https://www.temus.com/job-applicant-data-protection/)*