S3, Node.js, Kafka, Datadog, Redshift, Code, React, Typescript, Sqs, Postgres, Spark, Kubernetes on AWS, Debezium, Codex, Claude, GitLab CI, Knative, MCP

twilio , Apis, PostgreSQL, React, Typescript, Cloud Infrastructure, Stripe, Docker, Distributed Systems, FastAPI, Python, AWS, Scalable backend systems, Serverless Architecture, GitHub Actions, OpenAI APIs, AI agents, Workflow automation, Supabase, Event-driven architectures

mobile backend infrastructure, AI tools, data, Ai, Copilot, Claude, Code Cursor

Gerrit, Git, DDR, Pcie, post-silicon systems, Linux environments, memory subsystems, pre-silicon validation, caches, functional and stress tests, GDDR, DRAM technologies, AI-powered coding assistants

Java, Hibernate, CSS, Vue, Redux, Spring Boot, HTML, React Js, Docker, MongoDB, Kubernetes, LLMs, NoSQL databases, Claude, Tailwind, AI-assisted development tools, React Router

Databases, API design, Cloud Infrastructure, Containers, sandbox runtimes, tool-use orchestration, AI tooling, evaluation harnesses, internal libraries, eval pipelines, model gateways, LLM APIs, platform services, developer CLIs, prompt management, MCP integrations, agent architectures

Java, CSS, Scala, Kafka, Kotlin, HTML, React, Typescript, Javascript, Docker, Terraform, React Native, Rest Apis, Kubernetes, AWS, Event-driven architecture, AI-assisted development workflows, Go, AI coding agents, CI/CD

.Net Core, Database Design, PostgreSQL, Spring Boot, Angular, React, Docker, Terraform, MySQL, Flask, Python, AWS, Java, Express, Cloudformation, Dynamodb, Node.js, Redis, Django, Git, Gcp, MongoDB, Azure, Kubernetes, AI/ML infrastructure, Microservices architecture, Automated testing frameworks, SQL optimisation, Vector database technologies, CI/CD pipelines

Angular, React, Databases, Cloud Infrastructure, Typescript, Javascript, Docker, AWS, Node.js, Automated Testing, Vue.JS, Git, Gcp, Azure, Kubernetes, Infrastructure as Code, Frontend web development, Backend API development, CI CD, Next.js, AI-assisted software development tools, Monitoring, Production application support, DevOps practices, Automated deployment

data preparation , model selection , probability , Retrieval-Augmented Generation (RAG) systems, Large Language Models (LLMs), Tensorflow, Deep Learning, Git, Pytorch, Machine Learning, Python, Agents, Reasoning patterns, Optimization, Feature engineering, Production performance considerations, linear algebra, Maintainable code, Orchestration frameworks, Testing strategies