Software Development Engineer - R01571170

Software Development Engineer Job requirements • Proven experience building and shipping full-stack applications in a professional product-based environment. • Ability to independently own and deliver features or systems across sprint/release cycles. Mandatory Skills & Responsibilities • Strong hands-on experience with at least one modern backend stack, such as Java, Python, or Node.js/NestJS, with solid understanding of performance tuning, memory management, and concurrency. • Strong experience with modern frontend development using React and SSR-based frameworks where applicable, including routing, state management, and performance optimization. • Working knowledge of a major cloud platform such as GCP or Azure, including production deployments, containers, serverless services, messaging, IAM, and cost-aware operations. • Strong SQL fundamentals, including query optimization, indexing, schema design, and data modeling, with working knowledge of at least one NoSQL database. • Proven ability to design scalable and resilient systems using caching, load balancing, and event-driven architecture. • Comfortable working in an Agile/Scrum environment, with a track record of independently delivering features across sprints and releases. • Strong Git practices, including sensible branching strategies and clean release management. • Experience designing REST and/or GraphQL APIs, including versioning and backward compatibility. • Strong testing mindset, with experience in unit, integration, and contract testing. • Hands-on experience with Docker and container orchestration platforms such as Kubernetes. AI Skills: • Comfortable using AI tools in day-to-day engineering work to move faster, work smarter, and stay cost-aware while doing it • Familiarity with Retrieval Augmented Generation (RAG) architectures — semantic layers for data retrieval and grounding LLM responses in real, trustworthy data • Practical experience with at least one LLM application framework (LangChain, LangGraph, Google GenAI tools, or similar) for prototyping and integrating AI-driven features • Exposure to agentic or multi-agent AI systems — agent roles, tool use, memory, and workflow orchestration.