Forward Deployed Engineer - AI Prototyping & Product Engineering
Novartis (company site, opens in a new tab)8–12 yrsHyderabadOn-siteDirect career pageEst. 30–60 LPA
Posted 20h ago
Reach people at Novartis
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Novartis you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Translate complex life sciences and healthcare challenges into AI-powered product solutions from discovery through deployment and continuous improvement.
- Rapidly prototype, test, and refine AI applications using Python, TypeScript, React, foundation models, and reusable platforms with enterprise integration.
- Deploy and maintain secure, scalable AI applications on AWS with automated testing, monitoring, and adherence to privacy, security, and operational best practices.
Minimum Requirements
- 8-12+ years professional experience, with 5+ years delivering production software.
- Strong Python development skills for building complete production-ready AI applications beyond simple prototypes.
- Experience with TypeScript, JavaScript, React for building functional user interfaces.
- Strong engineering fundamentals including APIs, data modeling, databases, authentication, testing, containers, and cloud deployment.
Ideal Candidate Profile
- Proven product ownership from problem discovery through deployment and adoption in regulated environments is advantageous (life sciences, pharmaceuticals, healthcare).
- Experience building generative AI solutions including foundation models, retrieval-augmented generation, agentic workflows, and tool integrations.
- Hands-on with CI/CD, cloud services (especially AWS), and secure, maintainable AI product engineering in enterprise settings.