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
Robust 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.
Robust 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)

📌 Nous Infosystems (Bengaluru)
🏢 Nous Infosystems
📍 Bengaluru