AI FullStack Engineer

Location: Jaipur / Indore

Employment Type: Full-Time

Experience : 3 to 6 years

We are looking for a hands-on Senior Full-Stack AI Engineer who can independently design, develop, test, and deploy end-to-end Agentic AI applications using React.js and Python.

You will be responsible for taking a business requirement, breaking it into modules, deciding the application architecture, designing data structures and APIs, integrating AI components, and delivering a fully functional, production-ready solution.

We need someone who can think independently, make technical decisions, integrate services, and take complete ownership of the application lifecycle.

• End-to-End Development: Build complete AI applications using React.js for the frontend and Python for the backend.
• Solution Design: Understand business requirements, divide work into modules, and define application architecture, data structures, and API requirements.
• Agentic AI Development: Integrate LLMs, RAG pipelines, AI agents, tool calling, and frameworks such as Lang Chain and Lang Graph.
• Service Integration: Integrate third-party APIs, databases, AI models, MCP servers, and other required services and protocols.
• Database Design: Design and manage relational databases and vector databases based on application requirements.
• Deployment & Infrastructure: Handle end-to-end deployment, CI/CD pipelines, Docker, cloud infrastructure, and production releases.
• Testing & Quality: Perform end-to-end testing, including unit, integration, functional, and smoke testing, to ensure application reliability.
• Performance & Security: Monitor application performance, troubleshoot issues, and follow secure coding and deployment practices.
• Ownership & Communication: Work independently, communicate effectively with stakeholders, provide regular updates, and support off-hours activities when required by business needs.

• Strong hands-on experience with React.js, JavaScript/TypeScript, and modern frontend development.
• Strong Python programming skills with experience in Fast API, Django, or similar backend frameworks.
• Practical experience building and deploying end-to-end AI applications.
• Good understanding of LLMs, RAG, vector databases, prompt engineering, and AI agent workflows.
• Experience with frameworks such as Lang Chain or Lang Graph.
• Understanding of MCP, tool calling, function calling, and API integrations.
• Experience with SQL/NoSQL databases, REST APIs, and data modelling.
• Experience with Docker, CI/CD, cloud platforms, and production deployments.
• Hands-on experience with automated testing frameworks such as Py-Test and Jest.

• Can independently convert business requirements into a working technical solution.
• Can make decisions about architecture, data flow, APIs, AI components, and integrations.
• Is comfortable working across frontend, backend, AI, testing, and deployment.
• Has a problem-solving mindset and takes end-to-end ownership of deliverables.
• Has excellent communication skills and is willing to provide off-hours support when business requirements demand it.

Regards,

Chinmay

Date: Friday, 9 October 2026 at 7:34 AM

Subject: Re: JD for Senior Software Engineer

Hi Chinmay,

Are we looking for Senior full stack AI engineer or Architect ? Please go through the JD, sometimes it uses architect and sometime Sr. engineer.

Also is it too strict?

Thanks and Regards

Lalit

Date: Saturday, 3 October 2026 at 10:46 PM

Subject: JD for Senior Software Engineer

Location: Jaipur/Indore Type: Full-Time 

We are not looking for someone to simply build "wrappers" around LLMs. We are building high-sophistication, agentic systems that can reason, use tools, and execute complex multi-step workflows. You will be responsible for building the end-to-end infrastructure—from high-performance asynchronous backends and sophisticated RAG pipelines to sophisticated multi-agent architectures using the latest Model Context Protocol (MCP) standards.

You will work on Agentic AI driven insight platform that transforms complex data into actionable strategic roadmaps.

• Architect & Build Agentic Systems: Move beyond simple prompts. Design and implement agent architectures using LangGraph and custom frameworks that support long-term memory, tool/function calling, and task delegation.
• Advanced RAG Engineering: Build and optimize Retrieval-Augmented Generation pipelines, focusing on vector database mechanics, sophisticated ranking/re-ranking strategies, and citation accuracy.
• High-Performance Backend Architecture: Design scalable, distributed systems using FastAPI and AsyncIO, ensuring high concurrency and efficient multi-threading/multiprocessing for AI workloads.
• Full-Stack Productization: Develop polished, production-ready frontends (React/Next.js) that provide seamless interfaces for complex AI outputs and data-heavy dashboards.
• Observability & Evaluation: Implement rigorous LLM/Agent evaluation frameworks (Latency, Cost, Accuracy) using tools like Arize AI and LangSmith.
• Infrastructure & DevSecOps: Own the CI/CD pipeline, ensuring that deployments are automated, scalable (Kubernetes/Docker), and secure against modern vulnerabilities (SAST/DAST).

To be successful, you must possess a deep understanding of:

• Frontend: Expert-level React.js, Next.js (or Nuxt), TypeScript, Tailwind CSS, and Material UI.
• Backend & Systems: Mastery of Python (Django/FastAPI), AsyncIO, Concurrency/Parallelism, Pydantic, and SQLAlchemy.
• The AI Stack: Deep experience with OpenAI/Gemini/Claude SDKs, LangChain, LangGraph, and Agentic AI patterns (Multi-Agent Systems, Tool Use).
• Cutting-Edge Protocols: Experience or deep interest in the Model Context Protocol (MCP) and Agentic Development Workflows.
• Databases: Proficiency in both SQL (PostgreSQL, MySQL) and Vector Databases.
• DevSecOps & Cloud: Production experience with AWS/Azure, Docker, Kubernetes, and a "security-first" mindset (CVE Analysis, CI/CD Security Gates).
• Testing: A "Test-Driven" mindset. Proficiency in PyTest, Jest, and React Testing Library.

• The Architect's Mindset: You don't just write code; you think about systems. You understand how to structure data flow, optimize token limits, and design for "long-term memory" in AI agents.
• The Polyglot: You can move seamlessly between the nuances of a React frontend, a high-performance Python backend, and the non-deterministic nature of Large Language Models.
• The Perfectionist: You care about observability, evaluation metrics, and security—you want to build AI that is not only smart but reliable and production-ready.