AI Engineer Contractor

Key Responsibilities:
• Work closely with data science, engineering teams, and Front Office staff to design and implement AI solutions on Azure.
• Develop and deploy containerized solutions for AI deployments utilizing GitLab CI/CD pipelines.
• Advise on best practices for building scalable, secure, and efficient AI solutions.
• Initial focus will be delivering outcomes focused on retrieval-augmented generation (RAG).
• Fine-tune existing large language models (LLMs).
• Leverage financial data to develop predictive models, risk models, and other solutions that support investment decision-making.
• Assist in optimizing Azure infrastructure for performance and cost efficiency.
• Integrate AI models and tools into existing systems.
• Provide strategic guidance on AI and machine learning.
• Mentor and coach internal staff, helping them build proficiency with Azure AI tools and best practices.
• Lead training sessions and workshops to develop internal capabilities and foster a culture of continuous learning.

Qualifications:
• Minimum of 3 years of experience in AI engineering, with a focus on the Azure ecosystem.
• Previous experience in the asset management industry is required.
• Proficiency in Python and other relevant programming languages for AI development.
• Strong understanding of cloud architecture, data engineering, and containerization technologies (e.g., Docker, Kubernetes).
• Experience in the full machine learning lifecycle, from data collection to model deployment and monitoring.
• Solid knowledge of financial markets, asset management, and financial data (e.g., time series analysis, portfolio management, risk modeling).
• Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders.
• Proven experience mentoring and coaching teams, with the ability to elevate the technical skills of others.