Job Description

Software Engineer Generative AI Projects

About the Role

As a Software Engineer specializing in Generative AI projects, you will be involved in developing and deploying cutting-edge AI solutions within the Azure ecosystem. Collaborating closely with Data Scientists, AI Engineers, and DevOps you will integrate AI-driven capabilities into our business applications, ensuring they are scalable, secure, high-performing and high quality.

Our mission is to harness Artificial Intelligence to revolutionize enterprise processes, embedding AI deeply into our business framework. Your expertise in Azure services and AI/ML technologies will be crucial in realizing this vision.

Key Responsibilities

• Design & Development: Create, develop, and deploy AI/ML-based applications using Azure services.
• LLM Implementation: Develop and optimize Large Language Model (LLM) based solutions tailored to real-world business cases.
• API & Microservices Development: Build and maintain APIs and microservices to efficiently serve AI/ML-based solutions to customers.
• Software development: Streamline model operationalization, model inference backend development.
• Compliance: Ensure all AI solutions adhere to security, development and governance standards.
• Code Quality: Write and maintain unit tests, ensure robust test coverage, and enforce best coding practices (clean code, maintainability, and performance optimization).
• Technical Documentation: Create clear, concise technical documentation for developed components.
• Agile Practices: Work in Agile/Scrum teams to deliver high-quality applications on schedule.
• Collaboration: Work closely with Data Scientists and AI Engineers to integrate AI/L into business solutions

Required Skills and Experience

• At least 3 years of experience in a similar position
• Programming Proficiency: Strong command of Python for AI/ML development.
• Experience in AI/ML: Understanding of Generative AI, LLMs, ML, and (optionally) Natural Language Processing (NLP) technologies. Experience in deploying Generative AI, LLM and ML is an advantage.
• Azure Services: Experience with Azure AI/ML services, including Azure OpenAI, Azure Machine Learning, and Cognitive Services.
• Containerization: Familiarity with Docker, Kubernetes, and Azure Kubernetes Service (AKS) for deploying AI models.
• API Development: Proven experience in developing and maintaining RESTful APIs and microservices.
• DevOps Knowledge: Solid understanding of CI/CD pipelines and DevOps best practices within the Azure environment.
• Team Collaboration: Ability to thrive in an Agile environment and work effectively with multidisciplinary teams.
• Language Skills: Proficient in English (spoken and written), with a minimum level of B2.

Technology Stack

• Cloud & AI/ML: Azure OpenAI, Azure Machine Learning, Cognitive Services, Azure Data Factory, Azure Blob Storage, Azure DevOps, AKS.
• Development Tools: Azure DevOps, Databricks, Python, Docker, Kubernetes/AKS.
• MLOps: MLflow (Databricks).

Preferred Qualifications

• Vector Databases: Experience working with vector databases.
• Prompt Engineering: Knowledge of prompt engineering and strategies for LLM orchestration
• Code : Proficiency in Python code development in compliance with coding practises and industry standards.
• AI Security: Practical experience with AI security measures and model governance.

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