Description

You will define the architectural blueprint for AI systems at scale.

Responsibilities

• Establish cloud-native design principles, reference architectures, and best practices for AI workloads.
• Design secure, cost-optimized, high availability AWS architectures for AI Applications.
• Architect, design, and oversee the implementation of machine learning pipelines, from data ingestion to deployment.
• Lead proof of concepts (PoCs) for emerging AI capabilities (Gen AI, Agentic AI).
• Establish monitoring and observability frameworks using CloudWatch, Prometheus, Grafana, and Open Telemetry.

Required Skills

• 10+ years of experience in software/solution architecture, with 3+ years in AI/ML or data-driven applications.
• Hands-on experience with AWS services for AI/ML workloads (SageMaker, Bedrock, Lambda, EKS, Glue).
• Strong programming skills in Python and Java.
• Exposure to ML frameworks including TensorFlow and PyTorch.
• Familiarity with Generative AI, LLM, and vector databases (e.g., Pinecone, Cosmos, OpenSearch).
• Experience with AI/ML Ops, CI/CD Pipelines, and containerization.
• Experience with Model Tuning/Evaluation Techniques (Fine Tuning, RLHF) and RAG Implementations.

Key Skills

Education

Any Gradute