Sr. AI/ML Engineer (Generative AI, Machine Learning, AWS)

Infosys; Hyderabad, Pune District, Bengaluru; Hybrid; INR 2,500,000 - 3,800,000; Full time

Job summary

Infosys in Hyderabad invites a Sr. AI/ML Engineer (Generative AI, Machine Learning, AWS) with 5–9 years of hands-on experience to design, develop, and deploy cutting-edge AI solutions for business use cases.

You will work with LLMs, RAG, vector databases, and MLOps pipelines, building APIs and microservices, and ensuring scalable, production-ready systems on AWS SageMaker, Bedrock, Lambda, S3, ECS, and EKS.

Responsibilities

• Design, develop, and deploy Generative AI and Machine Learning solutions for business use cases.
• Build applications leveraging LLMs, RAG frameworks, and Vector Databases.
• Develop and optimize Prompt Engineering strategies for AI applications.
• Train, fine-tune, evaluate, and deploy machine learning models.
• Build scalable AI solutions using AWS services such as SageMaker, Bedrock, Lambda, S3, ECS, and EKS.
• Implement model monitoring, governance, and performance optimization mechanisms.
• Collaborate with Data Scientists, Developers, Architects, and Business stakeholders.
• Develop APIs and microservices to integrate AI capabilities into enterprise systems.
• Create and maintain MLOps pipelines for model lifecycle management.
• Conduct experimentation, benchmarking, and performance analysis of AI models.
• Ensure AI solutions are secure, scalable, and production-ready.
• Stay updated with emerging AI technologies and GenAI advancements.

Job description

Position: Sr. AI/ML Engineer (Generative AI, Machine Learning, AWS)

Experience: 5 to 9 years

Location: Hyderabad

Employment Type: Full-Time

Roles & Responsibilities

• Design, develop, and deploy Generative AI and Machine Learning solutions for business use cases.
• Build applications leveraging LLMs, RAG frameworks, and Vector Databases.
• Develop and optimize Prompt Engineering strategies for AI applications.
• Train, fine-tune, evaluate, and deploy machine learning models.
• Build scalable AI solutions using AWS services such as SageMaker, Bedrock, Lambda, S3, ECS, and EKS.
• Implement model monitoring, governance, and performance optimization mechanisms.
• Collaborate with Data Scientists, Developers, Architects, and Business stakeholders.
• Develop APIs and microservices to integrate AI capabilities into enterprise systems.
• Create and maintain MLOps pipelines for model lifecycle management.
• Conduct experimentation, benchmarking, and performance analysis of AI models.
• Ensure AI solutions are secure, scalable, and production-ready.
• Stay updated with emerging AI technologies and GenAI advancements.