1–5 years of experience in software engineering and production-quality Agentic AI Systems.
Experience of generating code using prompts and navigating fluidly through generated code using GitHub Copilot or OpenAI Codex or similar platforms
Design, build, evaluate, deploy, and maintain AI-enabled and agentic applications for enterprise use cases.
Develop backend services and orchestration layers using Python and frameworks such as FastAPI, Flask, or Django; TypeScript/Node.js experience is also valuable.
Collaborate with front-end teams using React, Next.js, Angular, or Vue.js to deliver high-quality user experiences.
Build AI application workflows that use LLMs, retrieval and grounding, tools, structured outputs, and APIs to complete business tasks reliably.
Build and integrate REST and/or WebSocket APIs and connect applications to internal and external tools, services, and enterprise data sources.
Requirements
Strong software engineering fundamentals and hands-on experience building production-grade applications, services, APIs, or microservices.
Proficiency in one or more backend languages such as Python, Java, or TypeScript/Node.js.
Experience with modern front-end frameworks such as React, Angular, Vue.js, or Next.js, or strong collaboration experience with UI engineers.
Experience designing and consuming REST and/or WebSocket APIs and integrating with databases, services, and external systems.
Hands-on experience with at least one major cloud platform such as Azure, AWS, or GCP/Vertex AI.
Interest in or hands-on experience building production AI systems, including LLM-powered features, agentic workflows, or intelligent automation use cases.
Experience applying software engineering discipline to AI systems, including testing, evaluation, iteration, and production readiness.
Experience using Git and standard engineering practices such as branching, code reviews, issue tracking, and CI/CD.