software engineering practices , Incident Response, Coding Standards, Operational Excellence, Generative AI, Prompting, Full Software Development Life Cycle, AI-assisted Development, AI Strategy and Prioritization, Evaluation and Inference Optimization, Cost and Latency Tradeoffs, Foundation Models, Agents and Tool Use, Testing and Operations, Orchestration Infrastructure, AI Leadership, Fine-tuning, AI-assisted Coding Review, Build Processes

.NET, Nunit, Mqtt, PostgreSQL, Mstest, Json, Sql, Microservices, Rabbitmq, Git, Web Applications, Docker, Distributed Systems, Xml, Selenium, Rest Apis, Azure, Kubernetes, Xunit, Playwright, Azure Service Bus, GraphQL APIs

platform development , Ml, Java, C, Javascript, Distributed Systems, Agile, Python, Ai

Object-Oriented Design (OOD/OOP), C, C++, Device Driver Development, JIRA, Git, Linux System Programming, Python, Software Architecture Design, Performance Optimization Debugging, Operating Systems Concepts, Scalable System Design, Linux GPU Kernel Driver Development, Linux Debugging Performance Analysis, Multithreading Concurrent Programming, Data Structures Algorithms, Kernel User Space Interaction, CI/CD, Embedded Linux System Software Development

Java, AWS Glue, Kafka, Redis, Sql, Google Cloud, Microservices, Elasticsearch, REST, Docker, Azure, Kubernetes, Spring Framework, AWS, AI tools

operational support , Google Cloud Platform, SLA, Linux, Cloud Architecture, Terraform, Distributed Systems, Incident Management, Microsoft Azure, Kubernetes, AWS, Networking, Infrastructure as Code, GitOps, On-Call operations, Rca, customer onboarding, infrastructure readiness, SLO, go-live governance, Customer Enablement operations, Troubleshooting, operational KPIs

data engineering , Gcp, MLops, Python, Sql, Distributed Computing, Orchestration, Data Governance, Data Lineage, Performance Monitoring, Lakehouse architectures, Automated alerting, MLOps platforms, Observability frameworks, Data quality metrics, Machine learning lifecycle, Data pipelines, CI/CD for machine learning systems

software engineering practices , Incident Response, Coding Standards, Operational Excellence, Generative AI, Prompting, Full Software Development Life Cycle, AI-assisted Development, AI Strategy and Prioritization, Evaluation and Inference Optimization, Cost and Latency Tradeoffs, Foundation Models, Agents and Tool Use, Testing and Operations, Orchestration Infrastructure, AI Leadership, Fine-tuning, AI-assisted Coding Review, Build Processes

Testing, Software Engineering, Coding Standards, inference and orchestration infrastructure, build processes, operations, generative AI, AI-assisted development

High Availability, C, Containers, Rib, Memory Management, Linux Networking, Linux Kernel, Python, fib, Linux OS internals, Kernel Networking Stack, p4, Go, network stack, ISSU, DPDK, Debian Build Packaging, Broadcom SDK