Job Description – AI/GenAI Developer (4+ Years Experience)
Job Title: AI/Generative AI Developer
Experience: 4+ Years
Job Summary
We are seeking an experienced AI/Generative AI Developer with a strong background in designing, developing, and deploying enterprise-grade Generative AI and Large Language Model (LLM) solutions. The ideal candidate should possess hands-on experience in Python-based backend development, LLM orchestration frameworks, prompt engineering, Agentic AI, FastAPI, and cloud AI platforms. Candidates must have worked on real-time AI projects and be able to clearly explain their technical contributions, architecture, and business use cases.
Mandatory Skills
- Python
- Generative AI (GenAI)
- Large Language Models (LLMs)
- Prompt Engineering
- FastAPI
- Agentic AI
- RESTful API Development
- LangChain and/or LlamaIndex
- Vector Databases (Pinecone, ChromaDB, FAISS, Weaviate)
- Git and CI/CD
Key Responsibilities
- Design, develop, and deploy scalable Generative AI and LLM-powered applications.
- Build AI-powered backend services using Python and FastAPI.
- Develop and maintain RESTful APIs and microservices for AI applications.
- Build intelligent AI agents using Agentic AI frameworks and autonomous workflows.
- Implement LLM orchestration using LangChain, LlamaIndex, or similar frameworks.
- Design effective prompt engineering strategies, including:
- Zero-shot prompting
- Few-shot prompting
- Chain-of-Thought (CoT)
- Function Calling
- Structured Output Prompting
- Integrate vector databases such as Pinecone, ChromaDB, FAISS, or Weaviate for Retrieval-Augmented Generation (RAG) applications.
- Develop and optimize RAG pipelines using embeddings and semantic search.
- Integrate AI solutions with cloud AI platforms such as AWS Bedrock, SageMaker, Azure OpenAI, or Google Vertex AI.
- Build secure, scalable, and production-ready AI services following microservices architecture.
- Collaborate with cross-functional teams to understand business requirements and translate them into AI-driven solutions.
- Write clean, maintainable, and well-documented code while following software engineering best practices.
- Participate in code reviews, testing, deployment, and CI/CD processes.
Required Technical Skills
- Strong proficiency in Python for backend and AI application development.
- Hands-on experience with FastAPI for developing scalable APIs.
- Extensive experience with Generative AI and Large Language Models (LLMs).
- Experience with OpenAI, Azure OpenAI, Anthropic Claude, Gemini, or similar LLMs.
- Strong understanding of prompt engineering techniques and LLM optimization.
- Experience with Agentic AI frameworks and multi-agent workflows.
- Hands-on experience with LangChain, LlamaIndex, or equivalent LLM orchestration frameworks.
- Experience implementing RAG architectures using vector databases.
- Strong understanding of embeddings, transformers, NLP concepts, and semantic search.
- Experience with REST APIs, microservices, and API integrations.
- Knowledge of cloud AI services:
- AWS Bedrock
- Amazon SageMaker
- Azure OpenAI
- Google Vertex AI
- Experience with Git, GitHub/GitLab, Docker, CI/CD pipelines, and containerized deployments.
Preferred Skills
- Experience with GraphQL APIs.
- Experience with TypeScript/Node.js for AI integrations.
- Knowledge of Kubernetes and container orchestration.
- Familiarity with AI observability, model monitoring, and evaluation frameworks.
- Experience with MCP (Model Context Protocol) and AI tool integrations is an added advantage.
Mandatory Candidate Screening Criteria
Candidates must have practical, hands-on experience in the following technologies:
- Python
- Generative AI (GenAI)
- Large Language Models (LLMs)
- Prompt Engineering
- FastAPI
- Agentic AI
Additionally, candidates must demonstrate:
- Hands-on implementation of these technologies in real-time production projects.
- Ability to clearly explain the project architecture, business problem, AI solution, and their individual contributions.
- Experience building production-ready AI applications rather than only proofs of concept.
- Strong understanding of end-to-end AI application development, including data flow, orchestration, deployment, and performance optimization.
Soft Skills
- Strong analytical and problem-solving abilities.
- Excellent communication and stakeholder management skills.
- Ability to prepare clear technical documentation.
- Strong collaboration skills and ability to work in Agile teams.
- Passion for AI innovation and continuous learning.
Interview Focus Areas
During the interview, candidates should be able to explain:
- End-to-end GenAI project implementation.
- RAG architecture and vector database selection.
- Prompt engineering strategies used in production.
- FastAPI-based AI service development.
- Agentic AI workflows and multi-agent systems.
- LLM orchestration using LangChain or LlamaIndex.
- Real-time production challenges, optimization techniques, and deployment strategies.
- Their individual contributions, technical decisions, and measurable business outcomes in previous AI projects.
Pay: ₹90,000.00 - ₹110,000.00 per month
Application Question(s):
- what is your current location and native?
- what is your total experience?
- what is your ctc and ectc
Work Location: Hybrid remote in Chennai, Tamil Nadu (Chennai, Chennai District)
