Generative AI Engineer

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., * 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.

• 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