Java, Docker, Node.js, Kubernetes, Python, DevOps practices and tools, Prompt engineering, Generative AI or LLM-based solutions

System Design, Application Development, Testing, Python, Cloud-native deployment patterns, Operational stability for ML or data-intensive systems

Sql, MLops, Gcp, Azure, Python, AWS, data pipelines, AI system design, LLMs, Cloud platforms, end-to-end AI solution development, CI-CD practices, RAG

snowflake , Sql, Amazon CloudWatch, AWS, Python, Docker, Git, LangSmith, API frameworks, Langfuse, MLflow, LLM systems, Snowpark, Snowflake Cortex, OpenTelemetry, Amazon Bedrock, AgentCore, LangChain, LangGraph

New Relic, Github, Azure Functions, Datadog, FastAPI, Python, Docker, Azure DevOps, Application Insights, Azure Monitor, Semantic Kernel, Azure OpenAI, OpenTelemetry, Azure Container Apps, Weaviate, AutoGen, LangChain, Azure AI Search, Pinecone, FAISS, Azure AI Studio

object detection , Machine Learning, Artificial Intelligence, Tensorflow, Numpy, Git, Pandas, Pytorch, Opencv, Image Processing, Python, Computer Vision, Segmentation, CNNs, Deep Learning Architectures, Vision Transformers

snowflake , Rust, Cursor, Sql, Typescript, Javascript, Terraform, Docker, Python, Azure DevOps, Schemachange, Cortex AI, Go, Claude Code, MLflow, CI CD, SageMaker, GitHub Copilot, GitHub Actions, SnowCLI

containerisation with Docker, secrets management, pipeline automation with Azure DevOps, networking and load balancing, relational and non-relational databases, developing production-grade backend services using Python, asynchronous programming frameworks, cloud provisioning frameworks such as Terraform or CloudFormation, infrastructure-as-code, LLM API gateway technologies, container orchestration such as ECS Fargate, identity and access management technologies, observability and monitoring tools, multi-provider integration across major cloud AI platforms