- Senior AI-Native Full Stack Engineer

Company: Nuaav

Location: India / Remote / Hybrid

Experience: 4-7 Years

Employment Type: Full-time

Company Overview

Nuaav is a boutique technology consulting firm focused on delivering innovative, scalable, and secure data engineering and AI solutions. We partner with corporate clients to drive impactful change through specialized expertise in product engineering, data systems, AI/ML, and user experience.

Our services emphasize personalized attention, agility, and quality, enabling clients to confidently transform and grow in evolving business environments.

Role Overview

We are seeking a highly skilled and hands-on AI-Native Full Stack Engineer with strong expertise in modern frontend and backend technologies, combined with proven experience building AI-powered applications and intelligent systems.

The ideal candidate is an AI-first engineer who can design, develop, and deploy scalable applications while leveraging Generative AI, Large Language Models (LLMs), Agentic AI frameworks, and AI-assisted development tools.

This role requires strong end-to-end engineering ownership, from building responsive user interfaces and scalable backend services to integrating AI models, developing intelligent workflows, and deploying production-ready solutions.

We are looking for someone who has built real-world AI-native products, rather than someone whose experience is limited to consuming third-party AI APIs or using AI coding assistants.

Key Responsibilities

Full Stack Engineering

- Design, develop, and maintain scalable, secure, high-performance full-stack applications.

- Build modern, responsive frontend applications using React.js, Next.js, TypeScript, and JavaScript.

- Develop robust backend services using Python (FastAPI/Django) and/or Node.js (Express/NestJS).

- Design and integrate RESTful APIs, microservices, and event-driven architectures.

- Work with relational and NoSQL databases such as PostgreSQL, MySQL, MongoDB, and Redis.

- Own complete feature development, from architecture and frontend implementation to backend integration, testing, and production deployment.

AI-Native & Generative AI Engineering

- Design, build, and integrate AI-native capabilities into enterprise-grade applications.

- Develop production-ready applications leveraging LLMs such as OpenAI GPT, Anthropic Claude, and other commercial or open-source models.

- Build and optimize Retrieval-Augmented Generation (RAG) pipelines, including document ingestion, embeddings, vector search, and contextual retrieval.

- Develop AI agents, multi-step reasoning workflows, and tool-calling systems using frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent technologies.

- Implement AI-driven automation,



conversational interfaces, intelligent assistants, and workflow orchestration.

- Integrate AI capabilities into frontend experiences, including streaming responses, conversational UIs, real-time interactions, and human-in-the-loop workflows.

- Implement model evaluation, prompt optimization, guardrails, monitoring, and cost/performance optimization to ensure reliable AI applications.

- Design secure integrations between LLMs, enterprise data sources, APIs, and external tools.

AI-Assisted Development & Engineering Practices

- Actively leverage AI-native development environments such as Cursor, GitHub Copilot, Claude Code, and MCP-based tooling to accelerate engineering workflows.

- Apply AI-assisted development practices across code generation, debugging, refactoring, testing, and documentation while maintaining engineering quality.

- Build reusable components, establish development best practices, and contribute to technical architecture decisions.

- Develop unit, integration, and automated tests to ensure application reliability.

- Collaborate with product managers, AI engineers, designers, and stakeholders to translate business requirements into working solutions.

Cloud & Deployment

- Build and deploy cloud-native applications on AWS, Azure, or Google Cloud.

- Work with Docker, CI/CD pipelines, serverless technologies, and cloud infrastructure.

- Ensure application security, scalability, observability, and production reliability.

- Troubleshoot performance bottlenecks across frontend, backend, and AI inference layers.

Required Qualifications

- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.

- 4+ years of hands-on software engineering experience with strong full-stack development expertise.

- Proven experience building and deploying AI-native or Generative AI applications in production.

- Strong frontend expertise in React.js, Next.js, JavaScript, TypeScript, HTML, and CSS.

- Robust backend development experience with Python and/or Node.js.

- Experience designing REST APIs, backend services, microservices, and integrating third-party systems.

- Strong working knowledge of SQL, relational databases, and NoSQL technologies.

- Practical experience integrating LLM APIs and implementing AI-powered application features.

- Hands-on experience with RAG, embeddings, vector databases,



prompt engineering, and AI orchestration frameworks.

- Understanding of agentic workflows, tool/function calling, and AI application architecture.

- Experience working with cloud platforms such as AWS or Azure.

- Familiarity with Git, CI/CD, Docker, testing frameworks, and modern software development practices.

- Hands-on familiarity with AI-assisted engineering tools such as Cursor, Claude Code, GitHub Copilot, or MCP integrations.

- Strong debugging, problem-solving, communication, and end-to-end ownership skills.

Preferred Qualifications

- Experience developing Agentic AI systems or multi-agent workflows using LangGraph, CrewAI, AutoGen, or similar frameworks.

- Knowledge of vector databases such as Pinecone, Weaviate, Chroma, FAISS, or pgvector.

- Experience implementing LLM evaluations, monitoring, guardrails, and production observability.

- Familiarity with structured outputs, function calling, Model Context Protocol (MCP), and AI tool integrations.

- Experience with WebSockets, streaming APIs, and real-time AI-enabled interfaces.

- Exposure to AWS Bedrock, Azure OpenAI, or managed AI infrastructure.

- Experience developing enterprise SaaS products, AI platforms, or intelligent automation solutions.

- Understanding of application security, authentication, authorization, and secure handling of sensitive data.

- Experience working in agile, fast-paced product engineering or consulting environments.

What Makes You a Strong Fit?

- You are equally comfortable building sophisticated frontend interfaces and architecting reliable backend systems.

- You have personally built and shipped AI-powered applications, not just experimented with LLM APIs.

- You understand how to move AI solutions from proof of concept to scalable, production-ready products.

- You actively use AI-native development tools to improve engineering productivity without compromising code quality.

- You take ownership of entire features and can independently solve complex engineering problems.

- You enjoy working at the intersection of software engineering, AI, and product innovation.

Why Work at Nuaav?

- Work on cutting-edge AI-native, Generative AI, and Agentic AI applications.

- Gain hands-on exposure to enterprise-scale product engineering and cloud technologies.

- Collaborate with experienced engineers, AI specialists, and technology leaders.

- Be part of a fast-growing boutique consulting environment that values innovation, agility, and technical ownership.

- Opportunity to build impactful AI-driven products and contribute to next-generation intelligent systems.

Interested candidates can share their profiles at [email protected]

Website: www.nuaav.com

📌 Full Stack Engineer (Noida)
🏢 Nuaav
📍 Noida