Job Title

Full Stack Developer – GenAI PortfolioCompany: Insight Global (on behalf of our client)Location: Remote - 10 am - 6 pm ist Compensation: 17–22 LPA (based on experience)Start Date: Immediate (No notice period preferred)Availability: Must be able to start within 2–3 weeks or soonerNotice Period: ASAP hire — only apply if you can start within 2 weeks of offerInterview Process: Priority scheduling for candidates who message on LinkedIn with their resumeIMMEDIATE JOINERS ONLYRole OverviewInsight Global is seeking a highly skilled Full Stack Developer to support a global consulting firm’s rapidly expanding GenAI portfolio. You will help design, build, and deploy custom AI‑powered platforms, including automation products like Proposal Excellence and other next‑generation GenAI tools.You’ll be working in a fast‑paced, experimental environment where agility, creativity, and strong engineering discipline are essential. This position is fully remote in India.Required Skills & Experience5+ years of full stack development experience (frontend + backend).Proficiency in Python, JavaScript/TypeScript, React, and Node.js.Hands‑on experience with GenAI/LLM technologies (OpenAI APIs, LangChain, embeddings, etc.).Experience building modern web applications and supporting internal tool adoption.Working knowledge of Kubernetes and containerized deployments.Strong understanding of API design, data integration, distributed systems, and microservices architecture.Comfortable working in agile environments with distributed global teams.Ability to thrive in a fast‑paced, experimental, highly collaborative environment.Key ResponsibilitiesFull Stack DevelopmentBuild and maintain full stack applications across both frontend and backend components.Develop scalable APIs, microservices, and data‑integrated features powering GenAI workflows.Support global teams with tool adoption, platform enhancements, and new feature rollout.GenAI / LLM EngineeringWork hands‑on with GenAI technologies such as OpenAI APIs, LangChain, embeddings, and LLM‑powered automation flows.Implement retrieval‑augmented generation (RAG) pipelines and integrate LLMs into end‑to‑end solutions.Cloud & DevOpsDevelop and maintain solutions using cloud platforms such as Azure, AWS, or GCP.Deploy and manage applications in Kubernetes environments.Contribute to CI/CD pipelines supporting reliable and iterative product releases.Team CollaborationWork closely with engineering, product, and global stakeholders in agile environments.Participate in rapid experimentation cycles with minimal supervision.