Generative AI Engineer

Job Description

Job Description Generative AI Engineer Job Description Job Title: Generative AI Engineer

Job Type: Full-Time
Experience: 2 6 Years
Location: [Location / Remote / Hybrid]
Department: Artificial Intelligence / Engineering

Job Summary

We are looking for a Generative AI Engineer to design, develop, and deploy AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and machine learning techniques. The ideal candidate should have strong Python programming skills and experience working with modern GenAI frameworks and cloud platforms.

Key Responsibilities

• Design and develop Generative AI applications using LLMs and foundation models.

• Build and deploy LLM-powered applications, AI agents, chatbots, and intelligent automation solutions.

• Develop RAG pipelines using document processing, embeddings, vector databases, and semantic search.

• Work with models such as GPT, Claude, Gemini, Llama, and other open-source or proprietary LLMs.

• Develop effective prompt engineering strategies and evaluate LLM responses.

• Implement model integration using APIs and SDKs.

• Fine-tune or customize models for specific business use cases when required.

• Build AI workflows using frameworks such as LangChain, LangGraph, LlamaIndex, or similar technologies.

• Develop APIs and backend services using Python, FastAPI, or Flask.

• Integrate AI solutions with databases, enterprise applications, and cloud services.

• Implement evaluation frameworks to measure accuracy, relevance, hallucination, latency, and cost.

• Monitor and optimize AI applications in production.

• Collaborate with product managers, software engineers, data scientists, and QA teams.

• Ensure responsible, secure, and scalable implementation of GenAI solutions.

Required Skills

• Strong programming experience in Python.

• Hands-on experience with Generative AI and Large Language Models (LLMs).

• Strong knowledge of:

  • Prompt Engineering

  • RAG

  • Embeddings

  • Vector Databases

  • Semantic Search

  • AI Agents

  • LLM APIs

• Experience with frameworks such as LangChain, LangGraph, or LlamaIndex.

• Experience working with vector databases such as Pinecone, FAISS, Weaviate, Milvus, or Chroma.

• Knowledge of REST APIs and backend development.

• Familiarity with Git, Docker, and CI/CD.

• Understanding of machine learning and NLP concepts.

Preferred Skills

• Experience with OpenAI, Azure OpenAI, Anthropic, Google Gemini, or AWS Bedrock.

• Knowledge of fine-tuning, LoRA/QLoRA, and model evaluation.

• Experience developing autonomous or multi-agent systems.

• Knowledge of MLOps/LLMOps.

• Experience with AWS, Azure, or Google Cloud.

• Knowledge of databases such as PostgreSQL, MongoDB, or Elasticsearch.

• Experience with AI safety, guardrails, responsible AI, and data privacy.

• Experience with PyTorch or TensorFlow.

• Knowledge of Kubernetes and cloud-native deployments.

Education

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a related field.

Key Competencies

• Generative AI & LLMs

• Python

• Prompt Engineering

• RAG

• AI Agents

• LangChain / LangGraph

• Vector Databases

• NLP

• Model Evaluation

• API Development

• Cloud & MLOps

• Problem Solving

• System Design