bedrock , MLops, SageMaker, Generative AI, AgentCore, Agentic technologies

Data Quality, MLops, Terraform, Docker, Python, Kubernetes, LLMOps, RAG, AI governance

snowflake , Sql, Databricks, Java, Solution Architecture, Grafana, Datadog, AWS, Prometheus, Restful Services, Software Engineering, Incident Management, Python, Azure, Gcp, SDLC Practices, Cloud Cost Optimization, Security-by-Design Principles, OpenAPI, Relational Databases, Architectural Artifacts, Observability Best Practices, OpenTelemetry, Cloud Data Platforms

Python, Devops, Docker, Git, MLops, vLLM, Cluster resource management tools, Retriever, SGLang, Model optimization techniques, NIM Factory Pipeline, CUDA optimization

Java, Apis, Tensorflow, MLops, Gcp, Pytorch, Docker, Spark, Keras, Azure, Kubernetes, Python, AWS, AI ML solutions, R, Dask

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

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

Networking, Operating Systems, cloud, Cybersecurity, Databases, Microservices, Cloud Computing, digital trust, LLMs, enterprise-level software development, Security Protocols, Ai, embodied AI, multimodal models, autonomous agents, Robotics, retrieval-augmented generation, human-machine interaction, data platforms, multi-agent orchestration, system architecture design, agentic AI, generative AI, physical AI systems, workflow automation