Forward Deployed Engineer - AI Prototyping & Product Engineering

Location: Hyderabad (Office)

Job Description Summary

Job Title: Forward Deployed Engineer - AI Prototyping & Product Engineering

#LI-Hybrid

Location: Hyderabad, India

Relocation Support: Yes

What if you could take an ambitious AI idea and turn it into a product that scientists, clinicians, and business teams actually use? In this hands-on, builder-first role, you'll work directly with teams across life sciences and healthcare to translate complex problems into practical AI-powered solutions. You'll move from discovery and rapid prototyping to full-stack product engineering, enterprise integration, deployment, and continuous improvement, using foundation models, AI-assisted development tools, retrieval-augmented generation, agentic approaches, and reusable platforms.

This is an opportunity to stay close to the code while shaping solutions with users and turning promising prototypes into secure, scalable products with measurable impact.

Key Responsibilities

• Partner with business and domain teams to translate complex challenges into high-value AI product opportunities.
• Rapidly prototype, test, and refine solutions through short build, demonstrate, learn cycles with users.
• Build end-to-end AI applications using Python, TypeScript, React, foundation models, and reusable platform capabilities.
• Apply AI-assisted development tools and coding agents while ensuring quality, security, and maintainable engineering.
• Develop retrieval-augmented generation, document intelligence, agentic workflows, and automation for life sciences use cases.
• Integrate AI products with enterprise application programming interfaces, data platforms, identity services, and authorized business systems.
• Deploy secure, reliable applications on Amazon Web Services using Amazon Bedrock and appropriate cloud services.
• Establish automated testing, evaluation, observability, continuous integration and deployment, and sustainable operational practices.
• Embed privacy, security, traceability, human oversight, and appropriate controls throughout the product lifecycle.
• Measure adoption and business outcomes, turning successful solutions into reusable capabilities that accelerate future AI products.