GenAI Engineer – LLM, RAG, Agentic AI & MLOps
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Job Description
Structured overview of role & requirementsAbout This Role
Lead design, training, fine-tuning, and deployment of large language models and multimodal AI agents for enterprise automation and insights.
Develop and automate scalable AI pipelines for real-time inference, retraining, model monitoring, and lifecycle management in cloud environments.
Collaborate cross-functionally to translate business use cases into operational scalable AI solutions ensuring performance, fairness, security, and compliance.
Minimum Requirements
5+ years of professional experience in enterprise AI/ML projects including LLMs, retrieval-augmented generation, and multimodal systems.
Proficient in Python (3.8+), deep learning frameworks (PyTorch, TensorFlow), and LLM tools (Hugging Face Transformers, LangChain).
Experience with cloud platforms (AWS, Azure, GCP) for deploying scalable AI models; preferred 3+ years supporting enterprise cloud deployment.
Bachelor’s or Master’s degree in Data Science, Computer Science, AI, or related technical field.
Ideal Candidate Profile
Experienced in managing end-to-end model lifecycle including training, fine-tuning, deployment, monitoring, versioning, and retraining workflows in cloud environments.
Skilled at implementing responsible AI practices such as bias detection, fairness assessment, and model security within regulated enterprise contexts.
Capable of leading and mentoring teams, working closely with cross-functional stakeholders, and documenting models for audit and compliance requirements.