Generative AI Engineer

Description

Job Summary: We are seeking an Azure OpenAI Specialist Engineer to implement and manage AI solutions on Azure, optimize applications, and stay current with innovations. Key Highlights: 1. Lead the implementation and management of AI solutions on Azure. 2. Collaborative work with multidisciplinary teams. 3. Training and development plan, including paid certifications. **General Description:** The Azure OpenAI Specialist Engineer is a key professional in our technology team. This individual is responsible for implementing, managing, and overseeing our Azure-based artificial intelligence solutions. This role requires deep expertise in Microsoft cloud technologies—especially Azure—and a solid understanding of OpenAI and its application in solving business problems. **General Mission or Objective of the Role:** The primary objective of the Azure OpenAI Specialist Engineer is to lead the implementation and management of our AI solutions on Azure. This professional will work closely with our development team to ensure our applications and systems are optimized to leverage Azure’s AI capabilities. The Azure OpenAI Specialist Engineer will also be responsible for staying abreast of the latest innovations in AI and cloud computing, and how these can be applied to enhance our products and services. We seek an Azure OpenAI Foundry and/or MosaicML Engineer with a minimum of 3 years’ experience implementing generative AI solutions in cloud environments, strong leadership skills, and the ability to translate business needs into language model (LLM)-based solutions. **Academic Qualifications** Bachelor’s degree in Systems Engineering, Computer Science, Mathematics, or related fields. Valued certifications (desirable): AI\-102: Azure AI Engineer Associate Databricks Generative AI Fundamentals MosaicML LLMOps Bootcamp / Open Source Model Deployment **Key Skills** Ability to translate business requirements into operational LLM-based solutions. Experience building reproducible, scalable, and governed workflows. Collaborative work with multidisciplinary teams (product, data, architecture). Proficiency in creating and deploying LLM models using Retrieval\-Augmented Generation (RAG) techniques. Agile mindset and capacity for continuous learning of new tools and models. Commitment to ethical and technical rigor in applying generative AI in sensitive contexts. Desirable experience in Natural Language Processing (NLP) or practical applications of generative AI. **Requirements** **Main Responsibilities** Consume, fine-tune, and integrate foundational models (e.g., GPT, Codex, Whisper, LLaMA, MPT) to address specific business use cases. Develop prompt engineering workflows and agent design for intelligent assistance, process automation, and content generation solutions. Implement fine\-tuning, RAG, embedding, and contextual grounding strategies using Azure OpenAI and MosaicML. Deploy models and pipelines as RESTful APIs using Azure Functions, Container Apps, or Databricks Model Serving (desirable). Establish version control, monitoring, and model governance mechanisms for production models. Collaborate closely with data, architecture, and security teams to ensure ethical, efficient, and secure use of generative AI. **We Offer** Competitive salary based on experience Indefinite-term employment contract Wellness and extra-legal benefits package (health, life, funeral insurance, etc.) Training and development plan Paid certifications ranging from 50% to 100% Workplace: Remote