Generative AI Engineer

We are looking for a highly skilled Generative AI Engineer with hands-on experience in building and deploying production-grade GenAI solutions. The ideal candidate should have strong expertise in LLMs, RAG, Agentic AI, AI Agents, Python, prompt engineering, and vector databases.

Key Responsibilities:

- Design, develop, and deploy end-to-end Generative AI solutions for enterprise use cases.

- Build and optimize Retrieval-Augmented Generation (RAG) pipelines.

- Develop LLM workflows, AI Agents, and Agentic AI solutions.

- Work with LLMs such as OpenAI/Azure OpenAI, Claude, Gemini, Llama, or equivalent models.

- Design effective prompt engineering strategies and optimize LLM responses.

- Implement document ingestion, chunking, embeddings, retrieval, reranking, and response-generation pipelines.

- Develop APIs and AI services using Python and FastAPI/Flask.

- Work with Vector Databases such as Pinecone, FAISS, Chroma, Weaviate, or Azure AI Search.

- Integrate GenAI solutions with enterprise data sources, applications, databases, and APIs.

- Implement LLM evaluation, guardrails, monitoring, security, and responsible AI practices.

- Deploy and manage GenAI applications on Azure, AWS, or GCP.

- Optimize AI solutions for accuracy, scalability, latency, reliability, and cost.

- Collaborate with business stakeholders, architects, data engineers, and AI teams to deliver production-ready solutions.

Required Skills:

- 412 years of overall technology experience with strong hands-on experience in Generative AI.

- Strong programming expertise in Python.

- Hands-on experience with LLMs, RAG, Prompt Engineering, AI Agents, and Agentic AI.

- Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar frameworks.

- Strong understanding of embeddings, vector search, semantic search, and vector databases.

- Experience integrating LLM APIs and enterprise data sources.

- Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, or equivalent AI platforms.

- Knowledge of FastAPI/Flask, REST APIs, Docker, Git, and CI/CD.

- Experience taking GenAI solutions from POC to production.

- Strong analytical, debugging, and problem-solving skills.