Senior AI Engineer

Hiring : Senior AI Engineer / GenAI Full Stack Engineer

Experience : 5-10 Years

Industry : Artificial Intelligence | Generative AI | Emerging Technologies

Employment Type : Full-Time

About the Role :

We are seeking a highly skilled Senior AI Engineer / GenAI Full Stack Engineer to design, develop, and deploy enterprise-grade Generative AI applications. This role requires strong expertise in full-stack development, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic AI systems, and cloud-native architectures.

The ideal candidate will have hands-on experience building production-ready AI applications using React.js, Python, FastAPI, OpenAI, Claude, vector databases, and modern cloud technologies.

Key Responsibilities :

1. Full Stack AI Application Development :

- Design, develop, and maintain scalable AI-powered web applications using React.js, Python, and FastAPI.

- Build end-to-end AI products from concept to production deployment.

- Develop highly responsive front-end interfaces for AI-enabled applications.

- Create robust backend services and APIs to support AI workflows and integrations.

2. Generative AI & LLM Engineering :

- Build and deploy production-grade Generative AI solutions using OpenAI, Claude, Gemini, or similar Large Language Models.

- Design prompt engineering strategies and optimize model performance.

- Evaluate and integrate emerging AI technologies and frameworks.

- Develop intelligent AI assistants, copilots, chatbots, and automation solutions.

3. RAG (Retrieval-Augmented Generation) Systems :

- Design and implement advanced RAG architectures for enterprise knowledge retrieval.

- Build retrieval pipelines with optimized chunking, indexing, embedding generation, and ranking strategies.

- Improve retrieval accuracy, relevance, and response quality.

- Implement hybrid search and semantic search capabilities.

4. Agentic AI & Autonomous Workflows :

- Develop and manage agentic AI workflows and multi-agent systems.

- Integrate external tools, APIs, and business systems with AI agents.

- Design autonomous workflows for complex reasoning and task execution.

- Build orchestration frameworks to support intelligent decision-making systems.

5. Vector Databases & Knowledge Systems :

- Implement vector search solutions using Pinecone, Qdrant, Weaviate, pgvector, or similar technologies.

- Design scalable knowledge management and semantic retrieval systems.

- Optimize indexing, retrieval speed, and query performance.

6. Backend Engineering & API Development :

- Develop scalable backend services using Python and FastAPI.

- Build secure and performant RESTful APIs and AI service integrations.

- Implement authentication, authorization, monitoring, and logging mechanisms.

7. Cloud, DevOps & Deployment :

- Deploy and maintain AI applications on AWS, Azure, or Google Cloud Platform.

- Containerize applications using Docker and manage deployments using Kubernetes.

- Implement CI/CD pipelines and infrastructure automation.

- Monitor application performance, reliability, and scalability.

8. Performance Optimization & Observability :

- Optimize AI applications for latency, throughput, cost efficiency, and token utilization.

- Implement observability, monitoring, tracing, and logging solutions.

- Continuously improve model response quality and application performance.

- Ensure production readiness and operational excellence.

9. Collaboration & Innovation :

- Collaborate with Product, Engineering, Data Science, and Business teams to deliver AI-driven solutions.

- Participate in architecture discussions and technology decision-making.

- Stay current with advancements in Generative AI, LLMs, and AI engineering best practices.

Required Candidate Profile :

- Strong experience in Full Stack Development using React.js, Python, and FastAPI.

- Hands-on experience building production-grade Generative AI applications.

- Expertise in OpenAI, Claude, Gemini, Llama, or similar LLM platforms.

- Strong knowledge of RAG architectures and semantic search systems.

- Experience with vector databases such as Pinecone, Qdrant, Weaviate, ChromaDB, or pgvector.

- Experience building agentic AI systems and AI workflow orchestration.

- Strong understanding of API development and backend architecture.

- Hands-on experience with Docker, Kubernetes, and cloud platforms.

- Strong problem-solving and system design capabilities.

Mandatory Skills :

- Generative AI (GenAI)

- OpenAI / Claude / LLMs

- React.js

- Python

- FastAPI

- Retrieval-Augmented Generation (RAG)

- Agentic AI

- Multi-Agent Systems

- Pinecone / Qdrant / Weaviate / pgvector

- Docker

- Kubernetes

- AWS / Azure / GCP

- API Development

- Prompt Engineering

Preferred Skills :

- LangChain

- LangGraph

- LlamaIndex

- MCP (Model Context Protocol)

- AI Agent Frameworks

- Vector Search Optimization

- MLOps

- AI Observability Platforms

- CI/CD Automation

Key Competencies :

- AI Application Development

- Full Stack Engineering

- LLM Engineering

- System Architecture

- Cloud-Native Development

- Problem Solving

- Innovation & Research

- Collaboration & Leadership

Why Join Us :

- Opportunity to build cutting-edge Generative AI products at scale.

- Work with the latest AI technologies, frameworks, and cloud platforms.

- High-impact role driving innovation and business transformation.

- Collaborative environment focused on AI-first product development.

Skills

Generative AI, Artificial Intelligence, LLM, RAG, Python, FastAPI, Agentic AI, VectorDB, AWS, React.js, Full Stack