bedrock , MLops, SageMaker, Large-scale system design, Generative AI, AgentCore, Architecting AI systems, AI solution delivery

software engineering practices , bedrock , Ml, Aws Services, MLops, Generative AI, AI workflows, AgentCore, architecture patterns, Agentic technologies, SageMaker, best practices

Apis, system integration, Python, Airflow, RAG embeddings, data pipelines, n8n, vector databases, make, Zapier, knowledge retrieval, workflow automation tools, LLM workflows, AI agents

Pytorch, Gcp, MLops, Docker, Azure, Kubernetes, Cloud-native engineering, Agentic AI frameworks, Prompt engineering, AI deployment, Hugging Face ecosystem, Structured tool calling, LLM evaluation and benchmarking, Generative AI application development, Workflow orchestration, RAG and knowledge retrieval systems, Inference optimization, Model fine-tuning or adaptation

Security Compliance, Cloud Infrastructure, DevSecOps, Scalability, Azure, AWS, Enterprise solution design, Software performance tuning, Software quality automation, Technology stack recommendations, Reusable components, Application architectural design, Software Application Architect, Development guidelines, Software architecture standards, Resilience engineering, CI CD practices, Architecture blueprints, Cloud Platform GCC

model selection , LLMOps tooling, multi-agent architecture, agent collaboration patterns, AI engineering standards, discovery mechanisms, retrieval-augmented generation, vector databases, prompt engineering, reference architectures, technical frameworks, retrieval architecture, agent design, LLM provider selection, integration patterns, agent mesh concepts