AI Platform Engineer

As an AI Platform Engineer at Distyl AI, your primary responsibilities include designing an AI-native platform that incorporates AI into its core principles, developing scalable services with a modern Python stack, advocating for strong software engineering practices, and collaborating with customer-facing teams to translate operational needs into platform features.

To qualify for the AI Platform Engineer position at Distyl AI, candidates should have 3-10 years of professional experience in software engineering, expertise in programming languages such as Python, Java, or Go, as well as strong experience with DevOps practices and a demonstrated eagerness to incorporate AI into their workflows.

In the role of AI Platform Engineer at Distyl AI, you'll work with a modern technology stack that includes programming languages like Python, Java, Golang, and tools like FastAPI, SQL Alchemy, and Kubernetes. Familiarity with cloud-native development and modern DevOps practices is essential for this position.

Absolutely! At Distyl AI, we provide a collaborative environment where engineers work alongside top professionals in AI and enterprise sectors. You'll have access to exciting projects that advance your skills and elevate your career while contributing to industry-leading innovation.

The work environment at Distyl AI is hybrid, giving you the flexibility to work three days a week in our San Francisco or New York City offices. We embrace collaboration and innovation, encouraging our team to explore new technologies and methodologies in a supportive setting.

In your response, highlight specific AI technologies you’ve worked with, such as machine learning models or frameworks you’ve implemented, and provide examples of how you incorporated these technologies into past projects to drive real-world impact.

When discussing your approach, emphasize your understanding of microservices architecture, containerization, and orchestration tools like Kubernetes. Share a specific example where you designed a scalable service and the benefits it provided.

Speak to agile methodologies, code reviews, test-driven development, and continuous integration/continuous deployment (CI/CD) practices. Provide examples of how adopting these practices improved product quality in your previous roles.

Choose a scenario that demonstrates your problem-solving skills, detailing the challenge's context, your thought process, and the strategies you employed to overcome it. Highlight the outcome and any lessons learned.

Discuss techniques such as performance optimization, thorough testing, and following secure coding guidelines. Share examples where you implemented these practices to improve code efficiency or bolster application security.

Identify the importance of actively listening to customer feedback, engaging with end-users, and translating these insights into actionable feature requirements. Give a specific example of when you successfully did this in a prior role.

Share your experience using AI tools like ChatGPT or similar resources to streamline development, automate repetitive tasks, or enhance code quality. Provide examples of how these tools improved your productivity or project outcomes.

Outline your understanding of DevOps principles, continuous integration, deployment pipelines, and how they enhance software delivery. Mention specific tools you've used and their impact on team performance.

Tailor your answer to reflect your technical skills, your passion for AI, and your eagerness to contribute to a cutting-edge AI platform. Highlight your collaborative nature and experience working with cross-functional teams.

Express your thoughts on AI's evolving role in the enterprise, highlighting potential advancements, challenges, and opportunities. Share your excitement about being part of this transformative journey as an AI Platform Engineer.