Senior Staff Forward Deployed AI Engineer - job 1 of 2

As a Senior Staff Forward Deployed AI Engineer at MongoDB, your primary responsibilities include leveraging Generative AI and LLMs to modernize legacy databases and enhance application functionalities. You'll work closely with enterprise customers to refactor applications, implement AI-driven features, and facilitate AI adoption across various industries. Additionally, this role requires you to prototype innovative solutions and contribute to the overall AI and software development strategy at MongoDB, ensuring that our offerings align with real-world customer needs.

To qualify for the Senior Staff Forward Deployed AI Engineer position at MongoDB, candidates should have a minimum of 8 years of experience in software engineering, with a robust skill set in Java, Python, and SQL. An engineering degree in fields such as Computer Science, Machine Learning, or Electrical Engineering is essential. Additionally, deep expertise in Generative AI concepts, alongside a proven track record of developing AI-powered applications and intelligent automation, is highly preferred.

In the role of Senior Staff Forward Deployed AI Engineer at MongoDB, you will have a significant impact on the company's AI strategy by providing insights gleaned from real-world implementations. Your work with enterprise clients will inform MongoDB's product roadmaps, ensuring that our solutions not only meet current demands but also drive forward the integration of AI in application development. Your hands-on experience will guide the maturation of AI frameworks within our offerings.

A Senior Staff Forward Deployed AI Engineer at MongoDB needs a combination of strong programming skills in Java, Python, and SQL, and a deep understanding of AI, specifically in areas like Generative AI, LLMs, and intelligent automation. Strong problem-solving capabilities are crucial, along with experience in modern software architecture, including microservices. Familiarity with test-driven development methodologies and a collaborative spirit are also essential for driving successful project outcomes with customers across various sectors.

Yes, MongoDB offers flexibility for the Senior Staff Forward Deployed AI Engineer role, allowing candidates to work out of the Sydney office or remotely from anywhere in Australia. This flexibility enables you to balance your professional responsibilities with personal commitments while still making a significant impact on our clients and the company's AI strategy.

When answering this question, provide a specific example that highlights your role in the project, the challenges you faced, and the results achieved. Discuss technologies used, such as Generative AI or LLMs, and explain how the implementation improved efficiency or functionality for the client.

Focus on your methodology for assessing current applications, identifying bottlenecks, and the steps taken to refactor code. Discuss specific techniques or tools you’ve used for performance optimization and any measurable outcomes from those efforts.

Provide an overview of projects where you’ve designed or worked with microservices architecture. Explain the advantages you've observed, such as scalability and maintainability, and discuss any challenges faced while transitioning from monolithic to microservices frameworks.

Describe a situation where you collected customer feedback and translated it into actionable product insights. Highlight how you communicated these insights to your team and the subsequent changes made to align the product with market needs.

Discuss the transformative impact of AI in application development, including enhancements in user experience, automation of processes, and the ability to analyze vast amounts of data. Give examples of technologies or trends, such as LLMs, that are leading the charge in this evolution.

Explain specific challenges encountered during legacy database migrations, such as data integrity issues or application compatibility. Discuss the strategies employed to overcome these hurdles and ensure a smooth migration process.

Discuss your commitment to code quality through practices such as test-driven development (TDD), code reviews, and automated testing. Explain how these practices help maintain standards and improve the overall reliability of the application.

Be prepared to discuss the AI tools and frameworks you are familiar with, like TensorFlow or PyTorch, and explain why you prefer them based on ease of use, community support, or specific features. Provide examples of projects where you've used these technologies.

Emphasize your communication and collaboration skills. Share an example where working with engineers, product managers, or customers improved a project outcome, focusing on the importance of understanding different perspectives and goals.

Discuss trends such as advancements in machine learning, natural language processing, and their applications in real-world scenarios. Show how your awareness of these trends influences your work and decisions in AI development.