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
- Solid 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)

📌 Nous Infosystems - Lead AI/ML Engineer - AWS Platform (Bengaluru)
🏢 Nous Infosystems
📍 Bengaluru