Senior AI & Full Stack Engineer
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Key skills for this role
About the Role
We are seeking a highly experienced Senior AI & Full Stack Engineer to design, develop, and deploy production-grade AI solutions and scalable enterprise applications. The role requires expertise in Python, FastAPI, LangChain, LangGraph, RAG, Node.
Key Skills for This Role
Responsibilities
- Design, architect, and deploy production grade AI agents and LLM powered enterprise applications
- Develop agentic workflows using LangChain, LangGraph, and Model Context Protocol
- Build and optimize Retrieval Augmented Generation pipelines
- Develop scalable AI and backend services using Python and FastAPI
- Integrate LLM based solutions with internal enterprise platforms, APIs, databases, and third party services
- Build multi channel AI assistants for web, mobile, WhatsApp, Microsoft Teams, text, and voice
- Develop scalable backend applications using Node.js, NestJS, Express.js, Laravel, and related technologies
- Create responsive frontend applications using React, Angular, and Vue.js
- Design and maintain RESTful and GraphQL APIs
- Design efficient database structures using PostgreSQL, MySQL, and MongoDB
- Deploy and manage applications on cloud platforms, particularly AWS EC2, S3, autoscaling, and related services
- Lead technical design discussions, code reviews, troubleshooting, and architecture decisions
Requirements
- Bachelor's degree in Computer Science, Information Technology, Software Engineering, or related discipline
- At least 8 10 years of software engineering experience
- At least 2 years of hands on experience developing AI, LLM, or agent based solutions
- Strong programming experience in Python
- Hands on experience with FastAPI or comparable Python web framework
- Practical experience with LangChain and LangGraph
- Experience designing and implementing RAG pipelines
- Strong backend development experience with Node.js, NestJS, Express.js, Laravel, or similar
- Frontend experience with React, Angular, or Vue.js
- Experience with PostgreSQL, MySQL, and MongoDB
- Experience deploying and managing applications in AWS or another major cloud environment
Full Job Posting
Role Overview
- We are looking for a highly experienced Senior AI & Full Stack Engineer to design, develop, and deploy production grade artificial intelligence solutions and scalable enterprise applications.
- The successful candidate will combine strong expertise in Python, FastAPI, LangChain, LangGraph, RAG, Model Context Protocol (MCP), Node.js, React, and Angular with extensive experience in backend architecture, API development, cloud deployment, database design, and technical leadership.
- The role is particularly suited to an engineer who has developed enterprise AI assistants, multi agent systems, conversational applications, and customer facing platforms across web, mobile, WhatsApp, Microsoft Teams, text, and voice channels.
Key Responsibilities
- Design, architect, and deploy production grade AI agents and LLM powered enterprise applications.
- Develop agentic workflows using LangChain, LangGraph, and Model Context Protocol.
- Build and optimize Retrieval Augmented Generation pipelines, including document processing, embeddings, vector search, retrieval, prompting, and response evaluation.
- Develop scalable AI and backend services using Python and FastAPI.
- Integrate LLM based solutions with internal enterprise platforms, APIs, databases, and third party services.
- Build multi channel AI assistants for web, mobile, WhatsApp, Microsoft Teams, text, and voice interactions.
- Develop scalable backend applications using Node.js, NestJS, Express.js, Laravel, and related technologies.
- Create responsive frontend applications using React, Angular, and Vue.js.
- Design and maintain RESTful and GraphQL APIs.
- Design efficient database structures using PostgreSQL, MySQL, and MongoDB.
- Deploy and manage applications on cloud platforms, particularly AWS EC2, S3, autoscaling, and related services.
- Lead technical design discussions, code reviews, troubleshooting, and architecture decisions.
Required Qualifications
- Bachelor’s degree in Computer Science, Information Technology, Software Engineering, or a related discipline.
- At least 8–10 years of software engineering experience.
- At least 2 years of hands on experience developing AI, LLM, or agent based solutions.
- Strong programming experience in Python.
- Hands on experience with FastAPI or a comparable Python web framework.
- Practical experience with LangChain and LangGraph.
- Experience designing and implementing RAG pipelines.
- Understanding of Model Context Protocol, tool calling, agent orchestration, memory, and structured outputs.
- Strong backend development experience with Node.js, NestJS, Express.js, Laravel, or similar frameworks.
- Frontend experience with React, Angular, or Vue.js.
- Strong understanding of REST APIs, GraphQL, microservices, and system integrations.
- Experience with PostgreSQL, MySQL, and MongoDB.
Preferred Qualifications
- Experience building enterprise AI assistants used by large numbers of users.
- Experience integrating AI applications with WhatsApp, Microsoft Teams, mobile applications, and voice services.
- Knowledge of vector databases and semantic search technologies.
- Experience with LLM evaluation, prompt testing, hallucination reduction, observability, and response quality monitoring.
- Understanding of AI security, data privacy, access control, and guardrails.
- Experience with Docker, Kubernetes, Redis, message queues, and asynchronous processing.
- Previous experience as a backend lead, technical lead, or engineering team leader.
- Experience modernizing legacy applications and migrating high volume databases.
- Exposure to SaaS, e commerce, government, logistics, customs, or enterprise digital transformation platforms.
Technical Skills
- AI and LLM: Python, LangChain, LangGraph, RAG, MCP, AI agents, prompt engineering, tool calling
- Backend: Node.js, NestJS, Express.js, Laravel, FastAPI, REST APIs, GraphQL, microservices
- Frontend: React, Angular, Vue.js
- Databases: PostgreSQL, MySQL, MongoDB
- Cloud: AWS EC2, S3, autoscaling
- DevOps: Git, CI/CD, Docker, Kubernetes
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