Generative AI Engineer

Job summary

Build and deploy scalable AI solutions, including large language model and retrieval-augmented generation applications. Manage the end-to-end machine learning lifecycle and create FastAPI-based services to deliver production-ready enterprise AI systems.

Job details

Job Summary AI Engineer with expertise in Generative AI, LLMOps, and MLOps, responsible for building and deploying scalable AI solutions, developing LLM and RAG applications, managing the end-to-end ML lifecycle, creating FastAPI-based services, and leveraging tools like Python, LangChain, PyTorch, Spark, Docker, and Kubernetes to deliver production-ready enterprise AI systems.

What you’ll do

Build and deploy scalable AI solutions, including large language model and retrieval-augmented generation applications. Manage the end-to-end machine learning lifecycle and create FastAPI-based services to deliver production-ready enterprise AI systems.

Requirements

The role calls for expertise in Generative AI, LLMOps, and MLOps, along with experience building and deploying AI applications. It also involves using Python, LangChain, PyTorch, Spark, Docker, Kubernetes, and FastAPI.

Listed skills

• Kubernetes · Preferred
• Docker · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Generative AI
• LLMOps
• MLOps
• Large Language Models
• Retrieval-Augmented Generation
• Python
• LangChain
• PyTorch
• Apache Spark
• Docker
• Kubernetes
• FastAPI
• Machine Learning Lifecycle
• AI Solution Deployment

Job areas

• Technology
• Software
• Data & Analytics
• Engineering
• Consulting