secure sdlc , Java, Machine Learning, Scala, Gcp, Azure, Python, AWS, deployment infrastructure, data pipelines, generative AI solutions, Regulatory Compliance, microservices architectures, live model lifecycle management, data engineering frameworks

MLops, Natural Language Processing, Data Warehousing, Computer Vision, Deep Learning, Data lakes, Infrastructure as Code, DevOps practices, ETL processes, AI ML technologies, CI CD

Networking, Storage, Cuda, Gcp, Azure, AWS, AI Enterprise software, sovereign AI infrastructure, inference deployment, MLOps pipelines, software stacks, NVIDIA DGX HGX systems, GPU-as-a-Service, GPU clusters, AI ML infrastructure

Ml, Devops, AWS, SageMaker, Ai, Quick Kiro, Amazon Bedrock

Devops, Migration, AWS, SageMaker, AI Enablement, modernization, AI ML services, Technical strategy, Amazon Bedrock

Nvme, NVMe-oF, KV-cache optimisation, CXL memory disaggregation, high-performance storage, low-latency network fabrics, infiniband, software-defined storage, memory platforms, RoCEv2, object and file systems, RDMA

Distributed Systems, Nfs, Salesforce.com, Networking Solutions, GPU-accelerated computing, G-Suite, AI HPC, AI ML workloads, Object File Storage, SMB protocols

model selection , Orchestration, Microservices, Gcp, Docker, Azure, Kubernetes, AWS, containerization technologies, tool calling, LLM-powered solutions, AI tooling, prompt engineering, agentic workflows, AI guardrails, context management, evaluation frameworks, event-driven architecture, distributed systems architecture

data engineering , Artificial Intelligence, Python, Sql, Pyspark, Devops, Api Integration, Microservices, Terraform, Azure Devops, Github, Kubernetes, Docker, Solution Architecture, Effort Estimation, Rfp, Rfi, Requirement Gathering, Solution Design, Cloud Architecture, Aws, Azure, Gcp, Data Architecture, Databricks, Etl, Resource Planning, Proposal Development, Stakeholder Management, Llm