Senior AI Engineer (Permanent)

CoreFactor is searching for a Senior AI Engineer on a permanent/full-time basis.

This position is hybrid and will require the successful incumbent to go into the office four (4) times per week.

We are seeking an experienced and technically strong Senior AI Engineer to join our clients Data AI & Analytics team. This role focuses on the applied use of Generative AI and Agentic AI leveraging existing large language models (LLMs) and platformsnot building models from scratch. As a senior member of the team youll 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:

Youll be building the agents and GenAI systems that CIs 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.
  

Education:

• Bachelors or Masters degree in Computer Science Data Science AI Machine Learning Statistics or a related field.
  

Experience:

• 48 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 limitationssuch as rate limits quota management retries/backoff and cost-per-callwhen 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).