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.

- Valuable 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.

📌 Domino PlatformSupport / Development Engineer (India)
🏢 TALPRO INDIA PRIVATE
📍 India