I
Technical Lead
I
Technical Lead
Infinite Computer Solutions India Pvt. Ltd.- Posted 3 days ago
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Job Description
Job Description
Responsibilities
- Framework & Tool Development: Design, develop, and maintain robust test automation frameworks, infrastructure, and internal tools using Java and Python, specifically tailored for Optical DWDM/OTN systems.
- Feature & Simulation Dev: Develop simulation tools, network element stubs, and mock environments in Java to mimic complex optical network behaviors, traffic patterns, and control plane protocols for comprehensive testing.
- Test Automation Engineering: Write, review, and implement clean, scalable automated test scripts with a strong emphasis on ODU/OTU or lambda-level switching functionalities.
- Cross-Functional Collaboration: Partner with hardware, firmware, and software design teams to define architecture requirements, test strategies, and comprehensive test plans early in the development lifecycle.
- Hardware Integration Testing: Configure, control, and automate operations for testing equipment (e.g., optical spectrum analyzers, power meters, traffic generators) using APIs, Java libraries, and Python scripts.
- End-to-End Validation: Perform system-level validation, including signal quality analysis, Bit Error Rate (BER) testing, and protocol compliance verification at the ODU/OTU or lambda level.
- Triage & Debugging: Analyze complex automation failures, isolate root causes across software/hardware boundaries, and work closely with core engineering teams to fix bugs.
- CI/CD Integration: Integrate Java- and Python-based automated test suites into continuous integration and deployment (CI/CD) pipelines to enable continuous testing and rapid release cycles.
- Education: Bachelor's or Master's degree in Computer Science, Electronics & Communications Engineering, IT, or a related technical field.
- Optical Domain Expertise: Strong foundational knowledge of Optical DWDM/OTN technologies, with in-depth understanding of ODU/OTU framing, multiplexing, and lambda-level switching concepts.
- Software Development Skills (Java & Python):
- Strong programming experience in Java (including Core Java, OOP concepts, multi-threading, concurrency, and data structures) for building simulation utilities or framework backends.
- Proficiency in Python for test automation, script development, and rapid prototyping.
- Testing Methodologies: Proven experience in software/hardware testing life cycles, test case design, and building scalable automation frameworks (e.g., TestNG, JUnit, PyTest, Robot Framework).
- Hands-on Hardware Experience: Direct experience interacting with lab equipment like optical spectrum analyzers, power meters, and network traffic generators (e.g., Ixia, Viavi, Spirent) via automated scripts or APIs.
- DevOps & Build Tools: Familiarity with Git version control, build tools (e.g., Maven, Gradle), and CI/CD pipelines (e.g., Jenkins, GitLab CI).
- Soft Skills: Strong analytical, troubleshooting, and problem-solving skills, with the ability to work effectively in a fast-paced agile development environment.
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About Company
Skills:
.Net Core, .NET 8-9, C#, Asp.net Mvc, Microservices, Javascript, App Services, Microsoft Azure, Azure DevOps, SQL Server, Css3, jQuery, Git, Html5, Incident Management, ASP.NET, Sitecore XM Cloud, Sitecore 9.x, Blob Storage, application performance monitoring, Azure AI Search, Application Insights, Azure Cache for Redis, RESTful Web APIs, Production Support, CI/CD pipelines
Skills:
Role-Based Access Control (RBAC), Prometheus, Grafana, Jenkins, RDBMS, Terraform, Ansible, AWS CloudFormation, Dynatrace, Microsoft Azure, Aws Cloud, Kubernetes, FinOps, GitHub Actions, ArgoCD
Skills:
storage optimization , Java, Nodejs, Microservices, AI tools, Caching, messaging systems, cloud scalability, GPT
Skills:
react.js , Java, PostgreSQL, Prometheus, Spring Boot, Kafka, Elk Stack, Grafana, Microservices, Rabbitmq, Git, JUnit, Mockito, Docker, MySQL, Restful Apis, Oracle, Kubernetes, AWS, Playwright, NoSQL databases, Cypress
Skills:
natural language processing (NLP), Machine Learning, Deep Learning, Tensorflow, Pytorch, Gcp, Azure, Python, AWS, model evaluation techniques, MLOps frameworks, cloud ML platforms