containerization , Docker, Automation Frameworks, Python, Java, Data structures, Algorithms, Gcp, System Design, Rest Apis, Azure, Kubernetes, Infrastructure as Code, AWS cloud services, Software design principles, Deployment technologies, Observability, Monitoring, Asynchronous processing, Generative AI, AI platform development, Workflow orchestration platforms, Backend distributed systems, Microservices architectures, Conversational AI, Platform reliability engineering, Event-driven architectures

FastAPI, AWS, Docker, Reactjs, Node, Cloud Devops, Concurrency, Experience with LLMs, Backend Python

Java, Apis, Kafka, Node.js, Spring Boot, Sql, Microservices, React, Performance optimisation, Reliability engineering, No-SQL databases, AI-assisted engineering tools, Observability, Event-driven architectures

.NET Standard Core, Typescript, Design Patterns, Cosmos DB, Cloud Services, Sql, Git, Continuous Delivery, Rest Apis, agile scrum development, AI-assisted development workflows, Microsoft development tools, advanced programming concepts, modern engineering productivity toolchains, object-oriented design, cloud-native application patterns, observability, developer automation, DevOps practices, system design tradeoffs, front-end platforms, test-driven development, unit testing frameworks, AI agents, intelligent automation, distributed service integrations

Google Cloud Platform, Kafka, Node.js, Microservices, Git, Typescript, Docker, Terraform, Rest Apis, LLM APIs, LangChain, NoSQL databases, prompt engineering, AI-assisted development tools, OpenAI APIs, Vertex AI, RAG, AI agents, ArgoCD, event-driven architecture

ECS, Grafana, Linux Networking, Terraform, Docker, Python, Go, EKS, Telemetry ingestion and analytics pipelines, GitHub Actions, AI-assisted engineering tools, tracing, Event-driven and serverless systems

Data Engineering Architecture and development of large scale data BI on cloud platforms ETL ie. DBT Dataform Informatica Talend and BI Looker Tableau PowerBI, Software Development, Ui Development, Machine Learning ML modeling or development experience with ML systems, Databases RDBMS NoSQL, Backend Design development and operation of APIs using Go or PHP, OSS contribution experience, Cloud development experience preferably GCP or AWS, Microservices architecture

Java, Microservices, Typescript, React, Distributed Systems, Python, Javascript, Go, AI ML technologies, LLMs, cloud-native applications, AI evaluation frameworks, embeddings, full-stack software engineering, agentic workflows, RAG, GraphQL APIs, semantic search, event-driven services

Cassandra, PostgreSQL, Docker, metrics, Python, Azure DevOps, Logging, Git, Gcp, Apache Kafka, MongoDB, Rest Apis, Azure Machine Learning, Azure, Kubernetes, Event-Driven Architecture, AI Agents, LangGraph, GitHub Actions, Model Deployment, Google Vertex AI, Azure AI Search, Distributed Tracing, LangChain, Retrieval-Augmented Generation RAG, FAST API, Model Monitoring, Prompt Engineering, Large Language Models LLMs, Vertex AI Vector Search, pgVector