Qualifications
Required Qualifications:Bachelor's Degree in Information Technology, Data Science, Machine Learning/AI, Computer Science, or a related field. At least 8 years of experience in data science and AI-related domains. Machine Learning & AI Expertise:Proficient in Large Language Models (LLMs) and building AI agents utilizing frameworks like LangChain, LangGraph, and LangSmith. Hands-on experience in prompt engineering, Retrieval-Augmented Generation (RAG), and LLM orchestration. Familiarity with AI agent design patterns including reasoning, planning, tool usage, and memory management. Demonstrated capability in designing, training, and deploying ML models in real-world production settings. Solid understanding of ML fundamentals and MLOps practices such as model versioning, monitoring, and CI/CD pipelines. Proficient in machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch). Programming Skills:Strong proficiency in Python. Experience with Java is a plus. Familiarity with data manipulation and analysis libraries (e.g., Pandas, NumPy). Cloud Computing:Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) for deploying AI models, with a preference for Azure. Software Development:Understanding of the software development life cycle (SDLC) and agile methodologies. Familiarity with version control systems (e.g., Git). Data Analysis:Adept at analyzing and interpreting complex datasets.
About the job
The Managed Port Calls team is seeking a Staff AI Engineer to spearhead AI innovation across the Marcura platform. This position is pivotal in architecting and delivering AI-driven features that significantly enhance operational efficiency, predictive analytics, and informed decision-making for our stakeholders.
As a hands-on role, you will be responsible for executing the development of production-grade AI systems, mentoring fellow engineers in AI/ML best practices, and selecting the most suitable technologies and frameworks. Collaborating closely with product, backend, and data teams, you will integrate intelligent solutions throughout the platform, ensuring our AI applications are scalable, reliable, and provide tangible business value.
Key responsibilities include:
- Transforming manual processes into fully automated systems.
- Implementing partial automation for processes where full automation is not feasible.
- Enhancing operational efficiency for both the operations team and clients.
- Minimizing repetitive manual tasks primarily for the operations team.
- Predicting outcomes based on existing historical data.
- Forecasting costs using historical information.
- Developing chatbot-style task automation.