Generative AI Engineer - Job DescriptionJob 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
