Develop and optimize backend services for AI and LLM-based applications

Integrate and manage LLM-based applications in cloud environments

Scale AI applications to meet performance and reliability requirements

Implement CI/CD pipelines to automate deployment processes

Monitor AI services to ensure performance and reliability

Establish observability and logging for tracking LLM API performance

Collaborate with DevOps teams to streamline workflows and improve system uptime

Work closely with AI and Data Science teams to enhance application functionality

Leverage cloud platforms, with a preference for Azure, to host and scale AI solutions

Design and develop APIs and microservices to enable AI-powered features

At least 3 years of experience in Machine Learning Engineering with a focus on software and backend systems

Strong expertise in integrating and working with OpenAI APIs and AI services

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

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

Deep understanding of cloud platforms, particularly Azure, as well as Apache Spark and Databricks

Strong Python programming skills for backend development

Experience in designing and implementing APIs and microservices architecture

Fluent English communication skills, both written and spoken, at a B2+ level or higher

Knowledge of Data Science principles and techniques

Experience working with Large Language Models (LLMs)

Familiarity with Natural Language Processing (NLP) concepts and applications