Senior AI Fullstack Engineer

Position: AI Full Stack Engineer

Experience: 7+ Years

Job Summary

We are seeking a highly skilled AI Full Stack Engineer with 7+ years of overall software development experience and strong expertise in building AI-powered applications. The ideal candidate should have hands-on experience in developing scalable web applications, integrating Large Language Models (LLMs), building AI agents, designing APIs, and deploying cloud-native solutions.

The role requires a combination of Full Stack Development, AI/ML Integration, Cloud Engineering, and DevOps expertise to build next-generation intelligent applications.

Key Responsibilities

AI & Generative AI Development

• Design and develop AI-powered applications using LLMs such as GPT, Claude, Gemini, Llama, or similar models.
• Build and deploy AI Agents, RAG (Retrieval Augmented Generation) solutions, chatbots, and intelligent automation platforms.
• Integrate AI models through APIs and frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar technologies.
• Develop prompt engineering strategies and optimize AI model performance.
• Implement vector databases and semantic search solutions
• .

Full Stack Development

• Design and develop scalable front-end applications using React.js, Angular, Next.js, Vue.js, or similar frameworks.
• Develop robust backend services using Python, Node.js, Java, .NET, or similar technologies.
• Build RESTful APIs, GraphQL services, and microservices architectures.
• Ensure high-quality code through code reviews, testing, and adherence to best practices.

Data & AI Infrastructure

• Develop and manage data pipelines for AI and analytics applications.
• Work with vector databases such as Pinecone, Weaviate, Chroma, Milvus, or FAISS.
• Design data ingestion, transformation, and retrieval processes.
• Optimize AI workflows for scalability and performance.

Cloud & DevOps

• Deploy and manage AI applications on AWS, Azure, or GCP.
• Implement CI/CD pipelines using GitHub Actions, Jenkins, GitLab CI/CD, or Azure DevOps.
• Utilize Docker and Kubernetes for containerization and orchestration.
• Monitor and optimize application performance, security, and cost.

Collaboration & Leadership

• Collaborate with Product Managers, Data Scientists, UX/UI teams, and business stakeholders.
• Mentor junior developers and promote engineering best practices.
• Participate in architectural discussions and technology evaluations.
• Contribute to technical documentation and knowledge-sharing initiatives.

Required Technical Skills

AI & Machine Learning

• Experience with Generative AI and Large Language Models (LLMs).

• Hands-on experience with:

• LangChain
• LangGraph
• CrewAI
• AutoGen

• Semantic Kernel

• Prompt Engineering and AI workflow design.
• RAG Architecture and Vector Search.
• Model evaluation and AI application optimization.

Programming Languages

• Python (Mandatory)
• JavaScript / TypeScript
• Java or C# (.NET) (Preferred)

Front-End Technologies

• React.js
• Next.js
• Angular
• HTML5, CSS3
• TypeScript

Back-End Technologies

• Python (FastAPI, Flask, Django)
• Node.js
• Spring Boot (Preferred)
• REST APIs & GraphQL

Databases

• PostgreSQL
• MySQL
• MongoDB
• Redis
• Vector Databases (Pinecone, Weaviate, Chroma, Milvus)

Cloud Platforms

• AWS
• Microsoft Azure
• Google Cloud Platform (GCP)

DevOps & Containerization

• Docker
• Kubernetes
• Git
• Jenkins
• GitHub Actions
• Azure DevOps

Preferred Qualifications

• Experience building AI Copilots, AI Assistants, or Agentic AI solutions.
• Experience with OpenAI, Anthropic Claude, Gemini, Llama, Mistral, or other foundation models.
• Knowledge of MLOps concepts and model deployment strategies.
• Experience with data engineering tools and frameworks.
• Understanding of AI governance, security, and responsible AI principles.
• Exposure to NLP, Computer Vision, or Recommendation Systems.

Soft Skills

• Strong analytical and problem-solving abilities.
• Excellent communication and stakeholder management skills.
• Ability to work independently and lead technical initiatives.
• Strong collaboration and mentoring capabilities.
• Adaptability to rapidly evolving AI technologies.

Nice-to-Have Certifications

• Microsoft Certified: Azure AI Engineer Associate
• AWS Certified Machine Learning S…