DevOps Engineer (Permanent)

CoreFactor is searching for a DevOps 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 AI/ML DevOps Engineer to join our clients Data, AI & Analytics team. In this role, you will help operationalize Gen AI and machine learning solutions by building and maintaining reliable CI/CD pipelines and production environments that support scalable AI applications. You will work closely with data scientists, AI engineers and data engineers to move AI solutions from prototype to production while meeting enterprise standards for reliability, security, and performance.

KEY RESPONSIBILITIES:

AI Solution Delivery & Production Deployment

• Enable the end-to-end delivery of AI, ML, and GenAI solutions, supporting use cases from early experimentation through scalable production.
  
  
  


• Partner with data scientists, AI engineers, data engineers, and data ops teams to move solutions from prototype to production-ready delivery.
  
  
  


• Support common AI solution patterns such as retrieval-augmented generation (RAG), search-driven applications, and AI-assisted or agent-based workflows.
  
  
  


• Contribute to reusable deployment approaches and solution templates that accelerate delivery across multiple AI initiatives.
  
  
  

CI/CD & Release Engineering (DevOps / MLOps Enablement)

• Support production deployments on Snowflake and cloud platforms (AWS or equivalent), including automated releases and environment separation.
  
  
  


• Build and maintain CI/CD pipelines using Jenkins and Bitbucket (or equivalent) to deploy AI/ML and data-driven applications.
  
  
  


• Support release practices including environment separation, deployment automation, and safe promotion across dev/test/prod.
  
  
  

Reliability, Monitoring & Operational Excellence (AIOps Mindset)

• Improve production readiness through monitoring, alerting, logging, deployment validation, and operational best practices.
  
  
  


• Troubleshoot production issues across pipelines, integrations, and AI applications; drive root-cause remediation and preventive improvements.
  
  
  


• Ensure solutions meet enterprise standards for security, stability, performance, and reliability.

Requirements

• Education:
  
  


• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical discipline, or equivalent professional experience.
  
  

Experience:

• 5–7 years of experience in DevOps, software engineering, platform engineering, or MLOps-related roles.
  
  


• Strong understanding of CI/CD concepts, release practices, and operational support in production environments.
  
  


• Hands-on experience building CI/CD pipelines with Jenkins and source control using Bitbucket (or equivalent).
  
  


• Proven experience deploying and supporting production systems.
  
  


• Experience working with data or AI platforms (e.g., Snowflake or equivalent), or strong interest in learning new platforms.
  
  


• Experience collaborating with AI/ML and data engineering teams to operationalize AI-driven applications and data-intensive workflows.
  
  


• Proficiency in Python, Bash, or similar scripting/programming languages.
  
  


• Familiarity with containerized environments (Docker).
  
  

Preferred Qualifications:

• Experience deploying AI or data-driven applications, including APIs, services, or lightweight user interfaces (e.g., Streamlit, React).
  
  


• Experience with integrations, authentication/authorization, and secure connectivity (e.g., SSO/OAuth, service accounts, API integrations).
  
  


• Exposure to Tableau or analytics/BI tools.
  
  


• Experience in financial services, fintech, or investment management.