Platform Engineer I

Role Overview

The graduate AI Engineer is responsible for developing innovative technical solutions, integrating generative AI technologies. This graduate role requires a basic understanding of modern technical and cloud-native practices, AI, and DevOps. You will support a wide range of customers through the “Ideation to MVP” journey, demonstrating eagerness to learn and contribute to a dynamic and innovative team.

Responsibilities

• Develop solutions leveraging GenAI technologies, integrating AI capabilities into cloud-native architectures.
• Assist in the design and implementation of GenAI-driven applications, ensuring integration with microservices and container-based environments.
• Create solutions that leverage the capabilities of modern microservice and container-based environments running in public, private, and hybrid clouds.
• Collaborate on technical projects with partners including Google, Microsoft, AWS, IBM, Red Hat, Intel, Cisco, and Dell/VMware.
• Support the engineering of GenAI solutions from ideation to MVP, ensuring performance and reliability within cloud-native frameworks.
• Assist in optimizing AI models for deployment in cloud environments.
• Contribute to the assessment of existing solutions and recommend technical treatments to transform applications with cloud-native/12-factor characteristics.
• Support the adoption of GenAI technologies within cloud-native projects.
• Contribute to authoring whitepapers, blogs, and speaking at industry events.
• Assist in providing guidance to clients on incorporating GenAI and machine learning into their cloud native systems.

Requirements

• A newly graduated developer with experience in Java or Python.
• Basic understanding of software development and exposure to AI/ML technologies.
• Familiarity with using GenAI frameworks and libraries such as OpenAI API.
• Basic experience in designing and optimizing prompts for AI models (Prompt Engineering).
• Strong verbal and written communication skills (English).
• Positive and solution-oriented mindset.
• Willingness to learn and grow within an Agile and Scrum project management environment.

Nice to Have

• Basic understanding of NLP techniques and tools, including tokenization, embeddings, transformers, and language models.
• Interest in Data Engineering for AI, including data preprocessing and feature engineering.
• Familiarity with AI ethics and bias mitigation.
• Basic understanding of Cloud-native technologies and DevOps practices.
• Willingness to pursue cloud and technical certifications from providers like Google, Microsoft, AWS, Linux Foundation, IBM, or Red Hat.

Skills

• Python
• Java
• OpenAI API
• GenAI
• NLP