Full-Stack Software Engineer

durable workflow orchestration, saga compensation, and fan-out/fan-in concurrency. - Develop async REST APIs, service layers, background workers, and workflow logic. - Build and maintain Go services, including gRPC servers, streaming RPCs, and cross-language integrations. - Model and query data in MongoDB using schemas, indexing, and aggregation pipelines. - Enhance and extend automated test frameworks based on product capabilities and new feature areas. - Convert test cases into automated modules; reproduce and diagnose issues in lab or production-like environments. - Frontend Engineering - Develop modern React/TypeScript frontends using component-based architecture, hooks, server-state management, and real-time data flows. - DevOps, Deployment & Observability - Deploy and operate services on Kubernetes with container best-practices, health checks, resource tuning, and rolling updates. - Implement observability with distributed tracing, metrics, and structured logging across

polyglot services. - Contribute to CI/CD workflows - GitHub Actions, Jenkins - across build, test, and deployment pipelines. - Capture, document, and maintain service inventories, deployment processes, and engineering metrics. - Quality Assurance & Validation - Build unit and integration tests, including async patterns and real-service validations. - Develop test strategies, execute test cases, log issues (JIRA, Bugzilla), and manage the defect lifecycle. - Test REST APIs and network automation scenarios (positive/negative paths) to identify defects and performance concerns. - AI-Enhanced engineering experience - Practical experience leveraging AI-assisted development tools (e.g., GitHub Copilot, code-generation assistants, static-analysis LLMs) to boost engineering productivity. - Incorporate AIOps to automate repetitive development tasks such as scaffolding code, generating tests, improving documentation, or analyzing logs/traces. - Experience applying AI-based inference tools to support development (e.g., summarizing complex code paths, generating refactoring suggestions, reasoning about defects and logs, assisting with API usage, type inference, or schema evolution). - Incorporate AI into the SDLC, including review security, workflows, code-quality safeguards, and validation of AI-generated outputs. - Familiarity with using AI tools to augment DevTest workflows, such as generating test cases, interpreting failures, or detecting patterns. Tech Stack - Languages: Python3, TypeScript, Go - Frontend: React19, Vite - Backend & Services: FastAPI/ASGI, gRPC, Protocol Buffers - Database: MongoDB (async drivers, indexing, aggregation pipelines) - Messaging: Kafka (producers/consumers) - Infra: Kubernetes, Docker, GitHub Actions, Jenkins - Observability: OpenTelemetry, Prometheus, structured logging - Network Automation (Plus): Netmiko, TextFSM, Nornir Qualifications - Proven years of professional software engineering experience. - Strong Python proficiency with async/await patterns (FastAPI or similar). - Experience with network automation tools such as Netmiko, TextFSM, or Nornir. - Production TypeScript/React experience - components, hooks, server-state libraries. - Working proficiency in Go (building and maintaining services). - Hands-on distributed systems experience - workflow engines, queues, saga patterns, eventual consistency. - CI/CD pipeline development using GitHub Actions or Jenkins. - Experience with MongoDB - schema design, async drivers, aggregation, indexing. - Solid understanding of Kubernetes and Docker. - Strong Pluses - Familiarity with routing and network protocols (BGP, VRFs