Principal, Data Science (Sr. AI Engineer)

We are seeking a hands-on AI Engineer to design, build, and deploy scalable AI and Generative AI solutions that accelerate innovation across Alcon R&D. The ideal candidate combines strong AWS Cloud expertise, professional AI coding skills, software engineering discipline, and end-to-end solutioning experience to address complex MedTech challenges.

Key Responsibilities:

• Design and develop AI and Generative AI applications using AWS services and modern AI frameworks.
• Build Retrieval-Augmented Generation (RAG), AI agent, copilot, and intelligent document-processing solutions.
• Develop secure, scalable APIs, microservices, and cloud-native applications.
• Drive technical solution design, architecture reviews, rapid prototypes, and production deployment.
• Implement MLOps and GenAIOps practices, including CI/CD, testing, monitoring, observability, and governance.
• Collaborate with R&D, Clinical, Regulatory, Quality, and Medical stakeholders to translate business needs into practical AI solutions.

Key Requirements/Minimum Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related technical field.
• 5-7 years of experience in software, cloud, data, or AI engineering, with hands-on delivery of production-grade solutions.
• Strong proficiency in Python and professional software engineering practices, including modular design, testing, code review, and AI-assisted coding.
• Hands-on AWS experience, preferably including Amazon Bedrock, SageMaker, Lambda, ECS/EKS, S3, API Gateway, OpenSearch, DynamoDB, Glue, Athena, and Step Functions.
• Experience with LLMs, prompt engineering, RAG architectures, vector databases, AI agents, and model evaluation.
• Experience developing REST APIs and microservices using frameworks such as FastAPI or Flask.
• Working knowledge of Docker, Kubernetes, GitHub Actions, Terraform or CloudFormation, and CI/CD pipelines.
• Strong analytical, problem-solving, communication, and stakeholder-management skills.

Preferred Qualifications:

• Experience in MedTech, healthcare, life sciences, clinical research, medical devices, quality, or regulatory environments.
• Exposure to responsible AI, AI governance, security, privacy, and regulated-data practices.
• Experience with knowledge graphs, Amazon Neptune or Neo4j, multimodal AI, and agentic frameworks such as LangGraph, CrewAI, or AutoGen.
• Relevant AWS certification in Solutions Architecture, Developer, Data, AI, or Machine Learning.

Success Profile:

• Technical Depth - Strong AI coding, AWS architecture, and production engineering skills.
• Product Mindset - Focus on user value, scalability, quality, security, and measurable outcomes.
• Solution Ownership - Ability to take use cases from discovery and design through deployment and support.
• Collaboration - Ability to work effectively with technical teams and MedTech R&D stakeholders.

Work hours: 1 PM to 10 PM IST

Relocation assistance: Yes