Lead Generative AI Engineer

Were supporting a major global financial technology organization thats making significant investments in AI innovation. Theyre scaling their engineering teams across North America to drive development of next-generation Generative AI solutions. Multiple openings are available for engineers at varying levels from early-career developers to senior leads and architects across areas like AI platform engineering, chatbot development, and data engineering for AI-driven systems.

Why This Role

This is a chance to be part of a global enterprise thats putting real resources behind AI strategy building tools, platforms, and models that impact client experiences and internal productivity at scale. Youll join a high-performing engineering group thats delivering enterprise-grade AI capabilities across multiple business lines.

What Youll Do

• Build and enhance production?grade AI and LLM?based systems for enterprise applications.
• Contribute to model fine?tuning, prompt optimization, and training workflows.
• Develop APIs, microservices, and SDKs for internal and client?facing AI products.
• Collaborate with engineering and data teams to operationalize AI solutions and support MLOps/LLMOps processes.
• Partner cross?functionally to design and deliver reliable, scalable AI integrations.
  
  

What You Bring

• Bachelors or Masters degree in Computer Science, Engineering, or related field (or equivalent practical experience).
• 4 years of hands?on Python development experience.
• Strong understanding of Generative AI, LLMs, and related model architectures.
• Experience working with NLP, model training, and fine?tuning workflows.
• Solid grasp of Linux environments and modern DevOps practices.
  
  

Nice to Have (Highlight These on Your Resume)

• Hands?on experience with frameworks like Flask, Django, or FastAPI.
• Familiarity with Python libraries such as numpy, pandas, scikit?learn, matplotlib, or opencv.
• Experience deploying AI solutions using cloud services like Azure OpenAI, AWS Bedrock, AWS Sagemaker, or Google Vertex AI.
• Background in AI/ML lifecycle management MLflow, Databricks, or Dataiku.
• Understanding of MLOps or LLMOps principles.
• Exposure to TensorFlow or PyTorch.
• Experience integrating AI models into enterprise or regulated environments.
• Familiarity with containerized cloud environments (Docker, Kubernetes).
• Version control experience with GitHub or Bitbucket.
• Bonus: experience working with conversational AI platforms (e.g., Copilot Studio, Kore.ai, Amelia).
• Experience collaborating with software development teams to embed AI into core applications.
  
  

Whats In It for You

• Join an organization thats putting real investment behind AI and automation initiatives.
• Work on cutting?edge technology in a large?scale, data?rich environment.
• Collaborate with top?tier engineers and data scientists driving AI innovation in financial technology.
• Opportunities for career growth across multiple teams and projects.
  
  

Seniority level

Mid?Senior level

Employment type

Full?time

Job function

Information Technology

Industries

Staffing and Recruiting

#J-18808-Ljbffr