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Bangalore, India
Actively hiring, first seen by us todayEmployment type in the employer’s posting: Full timeFrom the employer’s posting
Ability to take use cases from discovery and design through deployment and support.
Ability to work effectively with technical teams and MedTech R&D stakeholders.
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.
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
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Day 0
Early. Similar jobs usually come down between day 6 and day 69.
From 4,362 similar postings that came down. Coming down is not always a hire.
14 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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· 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.
Summary of Position: 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:
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.
· 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 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
· 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.
· 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.
· 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.
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We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Summary of Position:
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
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Bangalore, India
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