Domino Platform L3 Support / Development Engineer

Job Description

This is a remote position.

Domino Platform L3 Support / Development Engineer
Service Tower: Data & AI Platforms / Advanced Analytics
Experience: 7–10 Years
Role Type: L3 Support / Platform Engineering / Development Support
Domain Preferred: Life Sciences / Pharmaceutical / Regulated Environments
Immediate Joiners Only
Budget: Open
Location: Open
Work Mode: Open to all: Remote/Hybrid

Role Objective

We are seeking an experienced Domino Platform L3 Support / Development Engineer to provide advanced technical support and engineering expertise for the Domino Data Lab platform.

The role is focused on ensuring platform stability, performance, availability, and reliability for enterprise-scale Data Science, Advanced Analytics, and AI/ML workloads, particularly in a life sciences or pharmaceutical environment.

The ideal candidate should have strong hands-on experience in supporting data science platforms, troubleshooting complex production issues, managing ML workflow orchestration, and working with cloud-native technologies.

Key Responsibilities

L3 Platform Support & Incident Management

• Provide Level-3 support for complex Domino Data Lab platform incidents escalated from L1/L2 teams.
  
• Troubleshoot issues related to:
  
  • Workspace provisioning
    
  • Model execution
    
  • Job orchestration
    
  • Data connectivity
    
  • Platform performance
    
  • User access and environment issues
    
• Perform detailed root cause analysis (RCA) and implement permanent fixes for recurring issues.
  
• Ensure incidents and service requests are handled in line with defined SLAs and KPIs.
  

Domino Platform Operations

• Manage day-to-day operations of the Domino Data Lab platform.
  
• Support platform upgrades, patching, monitoring, performance tuning, and workspace management.
  
• Ensure high platform availability and uptime for enterprise data science users.
  
• Monitor platform health and proactively identify reliability or performance risks.
  

Data Science & ML Workflow Support

• Support data science environments and tools including:
  
  • Python
    
  • R
    
  • Git
    
  • Data science notebooks and workspaces
    
• Enable ML lifecycle activities such as:
  
  • Experimentation
    
  • Model training
    
  • Model execution
    
  • Deployment support
    
• Support analytics and AI/ML teams in resolving platform-level blockers.
  

Automation, Monitoring & Reliability

• Implement automation improvements to reduce manual platform support efforts.
  
• Enhance monitoring and alerting for platform health, usage, failures, and performance bottlenecks.
  
• Recommend and implement improvements to increase stability, reliability, and scalability.
  

Cloud & Container Platform Support

• Work with container and orchestration technologies such as:
  
  • Kubernetes
    
  • Docker
    
• Support cloud-based AI/ML platform integrations and workloads across:
  
  • AWS
    
  • Amazon SageMaker
    
  • Azure Machine Learning
    
• Assist with infrastructure-level troubleshooting related to cloud, containers, networking, and compute environments.
  

Required Skills

Mandatory Technical Skills

• Strong hands-on experience with Domino Data Lab platform.
  
• Experience supporting data science platforms and ML workflow orchestration.
  
• Strong troubleshooting and L3 production support experience.
  
• Hands-on experience with:
  
  • Kubernetes
    
  • Docker
    
  • Python / R environments
    
  • GitHub / GitLab / Bitbucket
    
• Cloud platform exposure, preferably:
  
  • AWS
    
  • Amazon SageMaker
    
  • Azure Machine Learning
    
• Understanding of data science and AI/ML platform operations.
  

Experience Requirements

• 7–10 years of overall IT experience.
  
• Minimum 4+ years supporting data science, analytics, AI/ML, or advanced analytics platforms.
  
• Experience working in life sciences, pharmaceutical, or regulated environments.
  
• Familiarity with:
  
  • GxP environments
    
  • ITSM tools
    
  • Change management
    
  • Release management
    
  • Incident and problem management
    

Nice to Have

• Kubernetes administration experience.
  
• Domino Data Lab certification.
  
• Cloud certifications in AWS or Azure.
  
• Exposure to:
  
  • Clinical analytics platforms
    
  • Research data platforms
    
  • AI/ML model development
    
  • Regulated data science environments
    

Soft Skills

• Strong analytical and problem-solving skills.
  
• Ability to work independently in high-priority production support situations.
  
• Good communication and stakeholder management skills.
  
• Ability to collaborate with data scientists, ML engineers, infrastructure teams, and business stakeholders.
  
• Strong ownership mindset and ability to work in SLA-driven environments.
  

Key Expectations

• Strong Domino Data Lab hands-on experience is highly preferred.
  
• Must be comfortable handling L3 platform incidents and RCA.
  
• Should have experience supporting enterprise AI/ML and data science workloads.
  
• Life sciences / pharma / GxP experience will be a strong advantage.
  

Requirements
Domino Data Lab