Design and enhance backend systems to support AI and LLM-based applications

Deploy and manage LLM applications within cloud environments

Optimize AI systems to meet performance and reliability standards

Develop automated deployment workflows using CI/CD pipelines

Monitor and maintain the stability of AI services

Establish observability and logging systems to track LLM API performance

Work with DevOps teams to enhance workflows and ensure system reliability

Collaborate with AI and Data Science teams to improve and expand application capabilities

Utilize cloud platforms, particularly Azure, to deploy and scale AI solutions

Create and implement APIs and microservices to enable AI-powered functionalities

A minimum of 3 years of experience in Machine Learning Engineering with a focus on backend and software development

Extensive experience integrating and working with OpenAI APIs and similar AI services

Proficiency in using MLOps tools such as Orion, ArgoCD, and Opsera for deployment automation

Hands-on experience with observability and monitoring tools, including Grafana, Dynatrace, and ThoughtSpot

Strong knowledge of cloud platforms, especially Azure, along with expertise in Apache Spark and Databricks

Advanced Python skills for backend development and implementation

Demonstrated experience in designing and building APIs and microservices architectures

Fluency in English, both written and spoken, at a B2+ level or higher

Understanding of Data Science principles and methodologies

Experience working with Large Language Models (LLMs)

Familiarity with Natural Language Processing (NLP) techniques and tools