Senior Full Stack Engineer (React + Python)

It's fun to work in a company where people truly BELIEVE in what they are doing! We're committed to bringing passion and customer focus to the business. Role: Senior Full Stack Engineer (React + Django) Fractal is a leading AI and analytics company that helps global enterprises turn data into decisions at scale. We are looking for a hands-on Senior Full Stack Engineer with 6+ years of experience to design, build, and scale enterprise-grade digital products across front-end, back-end, APIs, cloud, DevOps, and AI-enabled application layers. This role requires strong engineering ownership, practical design thinking, and the ability to deliver secure, reliable, and high-performing solutions in collaboration with architects, TPMs, and cross-functional teams. Role Brief:  You will own critical feature implementation across web applications, APIs, integrations, cloud-native services, and AI-powered capabilities. The role combines deep hands-on engineering with practical participation in technical design, code quality, performance optimization, and operational excellence. You will work closely with architects, TPMs, product managers, QA engineers, DevOps engineers, designers, and peer developers to translate solution intent into scalable, maintainable, and production-ready systems. Key responsibilities include: Develop robust, efficient, and maintainable code for critical features, ensuring both functional and non-functional requirements are met. Participate in system and solution design discussions, contributing practical implementation insights, technical trade-offs, and pseudo-code where needed. Act as a technical point of contact for day-to-day implementation issues, troubleshoot challenges quickly, and drive timely resolution. Enforce and improve code quality through code reviews, engineering standards, automated testing, and secure development practices. Collaborate closely with architects, TPMs, product teams, and platform teams to translate high-level designs and AI use cases into scalable, secure, and production-ready solutions. Build and integrate AI-powered application capabilities such as copilots, intelligent assistants, summarization, search, recommendations, and workflow augmentation using LLM APIs and related services where relevant. Implement AI-enabled solution patterns including prompt orchestration, retrieval-augmented generation (RAG), grounding strategies, structured outputs, tool or function calling, and quality or safety guardrails for enterprise use cases. Support and improve DevOps practices including build pipelines, CI/CD workflows, automated testing, release readiness, and engineering observability. Monitor, troubleshoot, and optimize application, system, and AI feature performance in line with project objectives, reliability expectations, latency targets, and cost considerations.