GenAI engineer

Role Overview: As a GenAI engineer at our company, your primary responsibility will be to architect, develop, test, and deploy generative-AI solutions for domain-specific use cases. You will design and implement agentic AI workflows and orchestration using frameworks such as LangGraph, Crew AI, or equivalent. Additionally, you will integrate enterprise knowledge bases and external data sources via vector databases and Retrieval-Augmented Generation (RAG). Your role will involve building and productionizing ingestion, preprocessing, indexing, and retrieval pipelines for structured and unstructured data. Key Responsibilities: - Implement fine-tuning, prompt engineering, evaluation metrics, A/B testing, and iterative model improvement cycles. - Conduct/model red-teaming and vulnerability assessments of LLMs and chat systems using tools like Garak (Generative AI Red-teaming & Assessment Kit). - Collaborate with MLOps/platform teams to containerize, monitor, version, and scale models (CI/CD, model registry, observability). - Ensure model safety, bias mitigation, access controls, and data privacy compliance in deployed solutions. - Translate business requirements into technical designs with clear performance, cost, and safety constraints. Qualification Required: - Bachelors / Masters / PhD in relevant field - Skills in Generative AI & LLMs, Python & ML Libraries, RAG & Vector Databases, Agentic AI Workflows, Data Pipelines, Model Evaluation, Red-teaming, Cloud Platforms, APIs, Microservices, Containerization, Data Governance, Security, and Orchestration Libraries. Good To Have Skills: - Fine-tuning & Parameter-efficient Tuning - Multimodal Models & Retrieval (Note: No additional details of the company were present in the provided job description),