Senior Specialist, Platform Analytics AI ( Python and AWS)

Novartis is hiring a Senior Specialist, Platform Analytics AI ( Python and AWS) in Hyderabad, India. Level rates it ; you can apply on Novartis.

Level's read on this job

Builds AI ●●●● is how Level rates this role: the job is building AI systems.
Tools and skills the posting cites include Bedrock, MLflow and SageMaker.
Level classifies it as a senior role.
Level lists 864 other open roles at Novartis.

AI in this role

Design, develop, and operate enterprise AI, GenAI, and MLOps platform capabilities and infrastructure.

BedrockMLflowSageMakerDatabricksPythonAWS

ml-opsai-automation

Job Description Summary

The Senior Specialist, Analytics AI role is responsible for the design, development, automation, and operational support of enterprise AI, GenAI, and MLOps platform capabilities. The role partners with business, architecture, security, data science, and engineering teams to deliver scalable, secure, and compliant AI platform services that accelerate the adoption of AI solutions across Novartis.
-Manage the end-to-end lifecycle of platform services including onboarding, provisioning, deployment, upgrades, support, monitoring, compliance, and retirement, ensuring reliable and governed operations.

-Partner with business, data, engineering, architecture, and security teams to translate complex business needs into platform capabilities, accelerating AI adoption and delivery of business value.

-Lead the implementation and governance of enterprise AI, data, and metadata management practices, ensuring secure, compliant, and trusted access to platform services and assets throughout their lifecycle.

-Demonstrate high agility in working across diverse business domains and technology landscapes, effectively communicating technical strategies, platform roadmaps, and business impact through executive presentations, dashboards, and storytelling.

Job Description

Major Accountabilities

Design, develop, and support scalable AI, GenAI, and Agentic AI platform capabilities that enable enterprise AI use cases.Build and operate MLOps, LLMOps, and AgenticOps capabilities to support model development, deployment, monitoring, and lifecycle management.
Develop reusable platform services including model serving, inference services, orchestration frameworks, APIs, observability, and automation capabilities.Design and implement cloud-native AI platform solutions leveraging AWS services and enterprise cloud platforms. Enable and support enterprise AI services including foundation models, agent-based workflows, model inference, and AI automation capabilities.
Develop and maintain platform APIs and automation services that enable self-service provisioning, deployment, and lifecycle management of AI resources. Drive platform automation across CI/CD pipelines, infrastructure provisioning, environment management, and deployment workflows.
Design, implement, and support Databricks-based ML and GenAI workflows, including MLflow, model serving, and workflow automation. Collaborate with data scientists, engineers, architects, security teams, and business stakeholders to deliver scalable and reusable platform solutions.
Support platform onboarding, deployment, migration, upgrade, and release activities while ensuring service continuity and operational stability. Ensure platform solutions comply with enterprise security, governance, quality, validation, and compliance requirements.
Implement monitoring, observability, incident management, and operational support processes to maintain platform reliability and performance. Evaluate emerging AI, cloud, automation, and platform technologies to enhance platform capabilities and engineering productivity.
Develop and maintain technical documentation, reference architectures, implementation standards, operational procedures, and user guidance. Act as a technical subject matter expert for platform capabilities and provide support for complex platform and cloud engineering challenges.
Proactively identify technical risks, dependencies, and operational issues and drive them to resolution in collaboration with relevant stakeholders. Communicate technical solutions, recommendations, and implementation approaches effectively to technical and non-technical audiences.
Partner with vendors and internal technology teams to evaluate platform capabilities and support continuous platform improvement initiatives. Ensure adherence to Novartis quality, security, risk management, and regulatory standards across all platform services and solutions. Contribute to a culture of innovation, automation, operational excellence, and continuous improvement within the AI Platform Engineering function.

Minimum Requirements

Experience in AI/ML Platform Engineering, MLOps, Platform Engineering, Cloud Engineering, or related software engineering disciplines.
Strong hands-on experience with AWS cloud services and cloud-native architecture patterns.
Experience with AWS Bedrock, Bedrock AgentCore, SageMaker, Databricks, MLflow, or equivalent AI platform technologies.
Strong programming and automation experience using Python and related development frameworks.
Experience building APIs, platform automation capabilities, infrastructure automation, and CI/CD pipelines.
Good understanding of AI/ML model deployment, inference patterns, lifecycle management, and production operations.
Experience with observability, monitoring, platform reliability, security controls, and governance practices.
Strong analytical, problem-solving, stakeholder management, and communication skills. Experience working in Agile, DevOps, and product-oriented delivery environments.

Why consider Novartis?
Our purpose is to reimagine medicine to improve and extend people’s lives and our vision is to become the most valued and trusted medicines company in the world. How can we achieve this? With our people. It is our associates that drive us each day to reach our ambitions. Be a part of this mission and join us!
Learn more here:

https://www.novartis.com/about/strategy/people-and-culture

Commitment to Diversity and Inclusion:
Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.
Join our Novartis Network: If this role is not suitable to your experience or career goals but you wish to stay connected to hear more about Novartis and our career opportunities, join the Novartis Network here:
https://talentnetwork.novartis.com/network

Skills Desired

Python (Programming Language)

How we rate this

Senior Specialist, Platform Analytics AI ( Python and AWS) at Novartis rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Specialist, Platform Analytics AI ( Python and AWS) is an open job at Novartis.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Hyderabad (Office).
The job was posted on September 8, 2026.
Seniority: senior.
Applications are handled by Novartis. Apply on Novartis

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ML OpsAI AutomationBedrockMLflowSageMakerDatabricksPythonAWS

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
Tell me about a workflow you automated with AI tools, end to end.
What are the limits of Bedrock that you've run into, and how did you work around them?
What's a project where you used MLflow hands-on?
Walk me through how you've used SageMaker in your day-to-day work.

Adapt your resume

List these exact terms on your resume: ML Ops, AI Automation, Bedrock, MLflow, and SageMaker. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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