NessOpen

AI Full Stack Engineer

Location
Bangalore, India, India
Last seen
Oct 21, 2026

About the role

Role: Senior Full Stack Developer, AI Applications Experience: 8-10 years Location: Gurugram, Haryana, India

Purpose

We are looking for a senior, technically strong Full Stack Developer who can independently design, build, maintain, and support AI-enabled applications for Finance Technology. The role requires end-to-end ownership of delivery, strong problem-solving skills, sound technical judgement, and the ability to work with business and technology stakeholders with minimal supervision. The candidate should have a good understanding of AI and Generative AI concepts and be able to translate practical use cases into secure, scalable applications.

Key responsibilities

Application build

- Design, develop, and ship full stack features across the UI, APIs, and data access layers. - Implement and extend AI-assisted workflows (chat, retrieval, document Q&A, copilots) using approved enterprise model access. - Write clean, tested TypeScript and Python, with reusable components rather than one-off scripts. - Design solutions for scalability, maintainability, security, observability, and supportability rather than focusing only on feature delivery. - Perform technical reviews, establish coding and engineering standards, and mentor less-experienced developers where required.

Independent delivery and technical ownership

- Own applications and enhancements end to end, including requirement clarification, solution design, development, testing, deployment, production support, and ongoing maintenance, with minimal supervision. - Independently manage technical issues, defects, environment problems, and production support; perform root-cause analysis and drive issues through to closure. - Work directly with business users, testers, architects, InfoSec, data, and integration teams; track dependencies, communicate status clearly, and proactively drive delivery. - Provide technically sound recommendations, challenge designs where appropriate, identify risks early (security, data handling, reliability, scalability), and propose practical solutions rather than waiting for direction.

Run and quality

- Maintain local and non-production environments, logs, and basic health checks. - Add unit and integration tests for new work, and regression tests for fixes. - Follow secure SDLC practice: no secrets in code, least privilege, and InfoSec-approved patterns only. - Document how each application is run, supported, and recovered.

Required experience and skills

- 8-10 years of relevant software development experience, with strong hands-on full stack development experience and demonstrated ownership of production applications end to end. - Strong hands-on expertise in a modern frontend stack, preferably React and TypeScript (Next.js is a plus), with the ability to design maintainable and user-friendly enterprise applications. - Strong backend development skills in Python (FastAPI or similar) or Node.js, including REST APIs, service design, error handling, performance, and integration patterns. - Strong working knowledge of SQL, APIs, JSON, authentication/authorization flows, Git, application architecture, debugging, and integration troubleshooting. - Good understanding and practical knowledge of AI and Generative AI, including LLM APIs, prompt orchestration, RAG, embeddings/vector search, document Q&A, copilots, and responsible enterprise AI patterns. Model research or training expertise is not required. - Strong analytical, problem-solving, stakeholder-management, and written/verbal communication skills, with the ability to work independently, prioritize effectively, and drive tasks to closure.

Preferred

- FastAPI, React, and TypeScript used together on the same product. - Experience with cloud platforms (preferably AWS), Docker, CI/CD pipelines, monitoring, and enterprise deployment practices. - Finance, reporting, or SAP-adjacent application support. - Hands-on experience with RAG, vector databases/search, enterprise LLM gateways, agentic workflows, AI evaluation, or AI observability.