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Showing 9 jobs
Skills:
containerization , Java, Golang, Distributed Systems, Python, next-generation databases, orchestration using Kubernetes, developer tools, DevOps practices, cloud-native applications, CI CD, event-driven programming paradigms, Managed Services, infrastructure as code
Skills:
.Net Core, Web Api, Amazon Web Services, Machine Learning, SQL Server, Jenkins, React, Nlp, MS SQL, Docker, Terraform, Elasticsearch, Elastic Search, Entity Framework, MongoDB, Restful Apis, Azure, Kubernetes, LLMs, Microservices architecture, GitHub Actions
Skills:
.NET, Java, Apis, Cloudformation, Microservices, ELT, React Js, Automated Testing, Apache Airflow, Typescript, DevSecOps, Docker, Terraform, Kubernetes, Python, Etl, AWS, Go, Next JS, Observability, Agile delivery practices, Event-driven architectures
Skills:
.NET, .Net Core, Docker, Distributed Systems, Rest Apis, Azure, Kubernetes, AWS, Observability platforms, Infrastructure as Code, AI-based developer productivity solutions, Microservices architecture
Skills:
.Net Core, Java, Kafka, Grafana, Microservices, Jmeter, Api Automation, Python, Performance Testing Tools, AI tools, distributed systems testing, k6, Locust, CI CD pipelines, event-driven architecture
Skills:
Jenkins, Git, REST, Spring Framework, Oracle Sql, Maven, Python, Angular Js, Java 1.7 or higher
Skills:
Automated Testing, Cursor, Microservices, Distributed Systems, Python, Java, Apis, Devops, CI CD, Microsoft Copilot, cloud-native architectures, Operational Excellence, observability, RAG architectures, Generative AI, LLMs, AI-assisted software development platforms, MCP servers, Claude Code, prompt engineering, Google Cloud platforms, GitHub Copilot, agentic workflows, AI governance
Skills:
Apis, Flask, FastAPI, Python, LLM-based systems, agentic workflows, GenAI, enterprise data systems, backend services, AI integrations
Skills:
model selection , Distributed Systems, Cloud Infrastructure, rollback experimentation, automated regression frameworks, fallback strategies, unconstrained interaction models, offline test sets, live traffic sampling, real-time performance monitoring, caching strategies, AI capability routing and orchestration, model serving infrastructure, ML inference infrastructure, intent orchestration, model and prompt release gating, latency optimization, Speech Processing, evaluation and quality assurance infrastructure, observability tooling, large-scale AI platform engineering, intelligent query classification
