Generative AI Solutions Engineer

The Managed Port Calls team requires a Staff AI Engineer to drive AI innovation across our Marcura platform.
This role exists to architect and deliver AI-powered features that enhance operational efficiency, predictive capabilities, and decision-making for stakeholders.
The role is hands-on execution—building production-grade AI systems, mentoring engineers on AI/ML best practices, and selecting appropriate technologies and frameworks.
Working closely with product, backend, and data teams, you'll embed intelligence throughout the platform while ensuring our AI solutions are scalable, reliable, and deliver measurable business value.
Sample use cases that the role will require to build and manage: Convert manual processes to fully automated processes Partially automate processes when full automation is not achievable Help improve efficiency for both operations team and customers Reduce the amount of manual (especially repetitive) work mainly for operations team Predict answers to questions based on an existing historical knowledge base Predict costs based on historical knowledge Chat bot style task automation Competitive Salary and Bonus : We reward your expertise and contributions.
Inclusive Onboarding Experience : Our onboarding program is designed to set you up for success right from day one.
Marcura Wellness Zone : We value your work-life balance and well-being.
Global Opportunities : Be part of an ambitious, expanding company with a local touch.
Diverse, Supportive Work Culture : We’re committed to inclusion, diversity, and a sense of belonging for all team members.
Bachelor's Degree in Information Technology, Data Science, Machine Learning/AI, Computer Science or other relevant fields Minimum of 8 years of experience in relevant fields including data science and AI Machine Learning & AI: Experience with LLMs and building AI agents using frameworks like LangChain, LangGraph, and LangSmith Hands-on experience with prompt engineering, RAG (Retrieval-Augmented Generation), and LLM orchestration Knowledge of AI agent design patterns: reasoning, planning, tool use, and memory management Proven experience designing, training, and deploying ML models in production environments Understanding of ML fundamentals and MLOps practices: model versioning, monitoring, CI/CD pipelines Proficiency in machine learning algorithms and frameworks (e.
g., TensorFlow, PyTorch).
Programming: Strong coding skills in languages such as Python, Good to have programming experience in Java, 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.
[Azure is the preference] Software Development: Understanding of software development life cycle (SDLC) and agile methodologies.
Experience with version control systems (e.
g., Git). Data Analysis: Ability to analyze and interpret complex datasets.
Problem-Solving: Strong analytical thinking to identify and solve operational inefficiencies.
Ability to design and implement AI-driven solutions.
Communication: Ability to explain complex technical concepts to non-technical stakeholders.
Strong written and verbal communication skills.
Collaboration: Experience working in cross-functional teams.
Ability to collaborate with other developers, data scientists, and business analysts.