CI Financial is seeking an experienced and technically strong Senior AI Engineer to join our Data, AI & Analytics (DNA) team. This role focuses on the applied use of Generative AI and Agentic AI, leveraging existing large language models (LLMs) and platforms—not building models from scratch. As a senior member of the team, you'll take technical ownership of intelligent applications and automation tools that use LLMs to solve business problems, set best practices for the team, and mentor junior engineers, while partnering closely with business, engineering, and governance stakeholders to bring production-grade AI solutions to life.  KEY RESPONSIBILITIES: Applied Generative & Agentic AI: You'll be building the agents and GenAI systems that CI's advisors, analysts, and operations teams actually rely on day to day — not prototypes that stall out after the demo. • Architect and build production-grade intelligent systems and applications using existing LLMs (e.g., OpenAI, Claude, Gemini, etc.) through API integration, prompt engineering, fine-tuning, or Retrieval-Augmented Generation (RAG). • Design, prototype, and lead development of agentic AI systems capable of multi-step reasoning, task decomposition, and tool use to automate and support complex business workflows. • Contribute to the design of a reusable, scalable AI platform (shared tooling, agent frameworks, and infrastructure) rather than one-off point solutions, so capabilities can be reused across use cases. • Building web app AI solutions using frameworks such as React or Streamlit. Monitoring & Improvement: • Set technical direction and best practices for GenAI and agentic solution design, including evaluation methodology, guardrails, and reliability of LLM-powered systems. • Drive continuous iteration and improvement of models and LLM-powered tools based on performance metrics, cost, and user feedback. Technical Leadership & Best Practices: • Lead design and code reviews, championing best practices around experimentation, reproducibility, and responsible AI. QUALIFICATIONS: Education: • Bachelor's or Master's degree in Computer Science, Data Science, AI, Machine Learning, Statistics, or a related field. Experience: • 4–8+ years of experience in a data science, machine learning, or AI engineering role, including hands-on experience delivering production systems. • Demonstrated experience designing, building, and shipping agentic AI systems involving multi-step reasoning, task decomposition, and tool use. • Experience designing around real-world infrastructure limitations—such as rate limits, quota management, retries/backoff, and cost-per-call—when architecting LLM-powered systems at scale. Skills: • Deep understanding of prompt engineering, RAG, fine-tuning, and evaluation of generative output, including tradeoffs across approaches. • Proficiency in Python and ML/AI libraries (e.g., Scikit-learn, PyTorch, TensorFlow). • Hands-on skills in designing and orchestrating agentic workflows (multi-step reasoning, task decomposition, tool/function calling). • Excellent communication skills; able to present complex technical concepts clearly to both technical and non-technical stakeholders, including senior leadership. • Experience with cloud-based environments (AWS, Azure, or GCP).​ This role follows our in‑office work model and requires employees to be onsite four days per week to support collaboration and business needs. This opportunity is for an existing vacancy with the company. The anticipated base salary range for this position is $69,500 - $119,500. Exact salary depends on several factors such as experience, skills, education, and budget. Salary range may vary based on geographic location. In addition to base salary, this position is eligible for participation in a bonus program. In addition, The Company offers a variety of benefits to eligible employees, including health insurance coverage, wellness programs, life and disability insurance, retirement savings plans, paid leave programs, education-related programs, paid holidays and vacation time, and many others. Many of these benefits are subsidized or fully paid for by the company.