Nous Infosystems - Lead AI/ML Engineer - AWS Platform

Nous Infosystems; Bengaluru; On-site; INR 2,400,000 - 4,200,000; Full time

Job summary

Nous Infosystems in Bengaluru seeks an experienced AI/ML Data Architect to design scalable data foundations for AWS SageMaker and Bedrock, and to implement RAG architectures for enterprise AI solutions.

You will collaborate with data scientists, ML engineers, data engineers and cloud architects to optimize workloads and ensure reliability, security and data quality in GenAI initiatives.

Qualifications

• Design and implement scalable AI data architectures.
• Hands-on experience with AWS AI/ML services.
• Strong understanding of RAG and GenAI architectures.
• Ability to optimize AI/ML workloads for performance and cost.

Responsibilities

• Design and architect scalable data foundations for AWS SageMaker and Amazon Bedrock.
• Develop and implement Retrieval-Augmented Generation (RAG) architectures for enterprise AI applications.
• Work with Agent Core and develop integrations with Claude-based models.
• Design data pipelines and architectures to support AI/ML and Generative AI workloads.
• Identify opportunities to optimize and fine-tune AI/ML workloads for performance, scalability, and cost efficiency.
• Collaborate with Data Scientists, ML Engineers, Data Engineers, and Cloud Architects.
• Evaluate AI/ML solutions and recommend AWS services and architecture patterns.
• Ensure AI solutions meet reliability, security, scalability, and data quality requirements.

Skills

AWS SageMaker

Amazon Bedrock

RAG (Retrieval-Augmented Generation)

Agent Core

Claude / LLM Integration

AI/ML Workload Optimization

Data Architecture for AI/ML

Tools

Vector databases

Embeddings

MLOps / LLMOps

Job description

• Design and architect scalable data foundations for AWS SageMaker and Amazon Bedrock.
• Develop and implement Retrieval-Augmented Generation (RAG) architectures for enterprise AI applications.
• Work with Agent Core and develop effective integrations with Claude-based models.
• Design data pipelines and architectures to support AI/ML and Generative AI workloads.
• Identify opportunities to optimize and fine-tune AI/ML workloads for performance, scalability, and cost efficiency.
• Collaborate with Data Scientists, ML Engineers, Data Engineers, and Cloud Architects.
• Evaluate AI/ML solutions and recommend appropriate AWS services and architecture patterns.
• Ensure AI solutions meet requirements around reliability, security, scalability, and data quality.

Key Responsibilities

• Design and architect scalable data foundations for AWS SageMaker and Amazon Bedrock.
• Develop and implement Retrieval-Augmented Generation (RAG) architectures for enterprise AI applications.
• Work with Agent Core and develop effective integrations with Claude-based models.
• Design data pipelines and architectures to support AI/ML and Generative AI workloads.
• Identify opportunities to optimize and fine-tune AI/ML workloads for performance, scalability, and cost efficiency.
• Collaborate with Data Scientists, ML Engineers, Data Engineers, and Cloud Architects.
• Evaluate AI/ML solutions and recommend appropriate AWS services and architecture patterns.
• Ensure AI solutions meet requirements around reliability, security, scalability, and data quality.

Mandatory Skills

• AWS SageMaker
• Amazon Bedrock
• RAG (Retrieval-Augmented Generation)
• Agent Core
• Claude / LLM Integration
• AI/ML Workload Optimization
• Data Architecture for AI/ML

Good To Have

• Generative AI / LLM applications
• Vector databases and embeddings
• AWS data services
• MLOps / LLMOps
• Prompt engineering
• Model fine-tuning
• Strong understanding of cloud-native AI architectures

Candidate Profile

• Strong experience designing AI/ML data and solution architectures.
• Hands-on experience with AWS AI/ML services.
• Strong understanding of RAG and enterprise GenAI architectures.
• Ability to optimize AI/ML workloads and work with emerging AI technologies.
• Excellent analytical, problem-solving, and stakeholder-management skills.

(ref:hirist.tech)