Sr. Operations Manager

Key Responsibilities 

• Own operations across the DSE, MLOps, and Agentic Ops portfolio; coordinate small teams of external application supporters and manage operational priorities. 

• Partner with product co-leads (Product Manager & Tech Lead) to align operational activities and outcomes with product roadmaps and business priorities. 

• Provide user support, incident management, and issue escalation, coordinating with Novartis teams and third-party providers for timely resolution. 

• Manage user community communications — proactive notifications on platform issues, model/agent updates, maintenance, and scheduled downtimes. 

• Own user training, onboarding, and offboarding coordination across analytics platforms, MLOps tooling, and agentic frameworks. 

• Perform platform, model, and agent performance monitoring, storage hygiene, and vulnerability management; manage incident detection, response, and resolution. 

• Lead access, authentication, and authorization management, and Responsible-AI guardrails (prompt security, data-leakage, audit trails), in alignment with Novartis security, compliance, and AI governance standards. 

• Test key functionalities after upgrades, patches, and framework releases, in collaboration with internal Novartis teams or third-party providers. 

• Collaborate with the DSE Product Team, CSE/HPC teams, AI/ML engineering, and BR Compute Management for direction, alignment, and prioritization. 

• Deliver regular usage, license, model, and agent utilization reports and status updates to product leads and the BR Compute Management Team. 

• Drive adoption of best practices, automation, FinOps discipline (compute/GPU/token cost), and AI-assisted operations to enhance team efficiency, user experience, and service quality. 

• Maintain and extend user documentation, wikis, publishing guides, setup instructions, internal SOPs, and best-practice guidance.

Platform-Specific Responsibilities

• Administer the Plenty platform — reliability, performance, secure operations, user lifecycle, and model lifecycle management as a core MLOps capability. 

• Manage the lifecycle of the Posit Suite (RStudio / RSConnect) — maintenance, configuration, upgrades, patching, and backup validation. 

• Support RSConnect publishing needs — dashboards, model/API endpoint deployment, and user access management. 

• Manage the lifecycle of Python & JupyterHub environments and kernels, coordinating with HPC evolution cycles for aligned user experiences. 

• Support users with HPC/GPU access, ML training workflows, and notebook-based applications (e.g., Dash, Streamlit) and their promotion to RSConnect. 

• Drive DSE platform improvements — containerization, IDE integration, and MLOps-friendly workflows such as experiment tracking and reproducible environments. 

• Enable model lifecycle capabilities across the DSE portfolio — versioning, deployment, monitoring, drift detection, and retirement — and help industrialize experimental workflows into governed MLOps pipelines. 

• Support the early-stage operations and enablement of agentic AI platforms (e.g., Biomni) as this capability evolves — helping onboard agent frameworks, LLM backends, tool integrations, and vector/RAG components. 

• Contribute to access, guardrail, and audit-trail practices for agentic AI, and track agent execution, token/compute consumption, and cost. 

• Coordinate integration with HPC, DGX, and cloud compute back-ends used by data science, ML, and agentic workloads. 

Required Qualifications & Experience  

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Computational Sciences, or a related discipline. 
• 7+ years of hands-on experience operating data science / analytics / ML platforms in a research or enterprise environment, with at least 2+ years in a lead/co-lead operations role spanning DSE and/or MLOps. 

• Strong Linux system administration and scripting skills (Bash, Python). 

• Hands-on experience with Posit/RStudio Workbench, RSConnect, JupyterHub, and Python/R environments. 

• Demonstrated experience with MLOps/LLMOps practices — model lifecycle management, model registries, CI/CD for ML, monitoring, and drift detection. 

• Experience managing containerized environments and orchestration. 

• Exposure to or interest in agentic AI frameworks and platforms such as Biomni, with a willingness to grow this capability alongside the team. 

• Working knowledge of vulnerability management, patching, and identity/access management (LDAP/AD, SSO, RBAC). 

Preferred Qualifications 

• Experience supporting life sciences / drug discovery workloads (genomics, cheminformatics, computational biology, AI-assisted research). 

• Exposure to HPC and GPU platforms as back-ends for data science workloads. 

• Familiarity with observability/monitoring tools. 

• Experience with cloud data science services and FinOps practices. 

• Knowledge of Responsible AI and model governance frameworks. 

• Prior experience in a regulated pharma/biotech research environment 

Commitment to Diversity and Inclusion / EEO paragraph  

Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.  

Accessibility and accommodation 

Novartis is committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the recruitment process, or in order to perform the essential functions of a position, please send an e-mail to diversityandincl.india@novartis.com and let us know the nature of your request and your contact information. Please include the job requisition number in your message