Forward Deployed Engineer

As a Forward Deployed Engineer at Braintrust, you will lead professional services engagements for both new and existing customers. Your key responsibilities include implementing evaluation frameworks tailored to customer use cases, building integrations with customer data pipelines, and guiding best practices for model evaluation and testing. You'll also collaborate with internal teams to influence product development based on customer insights.

To apply for the Forward Deployed Engineer position at Braintrust, candidates should have 2-5 years of experience in software engineering, ML engineering, or technical consulting. Proficiency in Python or TypeScript and familiarity with machine learning workflows and model evaluation are essential. Strong communication and project management skills, along with a self-starter mindset, are highly valued.

Essential technical skills for a Forward Deployed Engineer at Braintrust include proficiency in programming with Python or TypeScript, understanding of machine learning evaluation processes, and experience with model integration. Candidates should be comfortable writing custom evaluators, defining metrics, and building evaluation pipelines for AI models.

The Forward Deployed Engineer role at Braintrust is pivotal for customer success, as it involves directly collaborating with clients to implement AI evaluation frameworks that meet their specific needs. By constructing integrations and providing best practices, you ensure that customers can effectively leverage Braintrust’s platform, thereby enhancing their operational efficiency and model performance.

As a Forward Deployed Engineer at Braintrust, you can expect a dynamic, hybrid work environment where you’ll engage with top-tier enterprise customers. Our culture encourages collaboration with a close-knit, mission-driven team of experts, providing a supportive and innovative atmosphere focused on solving impactful problems in AI.

When answering this question, detail the project's objectives, your specific role, and the evaluation framework you implemented. Highlight the methodologies you used, the challenges faced, and how you collaborated with the customer team to achieve successful outcomes.

Discuss your process of assessing customer needs, understanding their data pipelines, and identifying the tools required for seamless integration. Emphasize any specific technologies or frameworks you have used and how your approach ensured system compatibility and performance.

Mention key metrics such as accuracy, precision, recall, F1 score, and whatever is relevant to the model's purpose. Explain why these metrics are important and how you would collect and analyze data to assess model performance effectively.

Share a specific example of a challenge, the steps you took to identify the issue, and how you collaborated with the customer to implement a solution. Assessing the impact of your efforts and the outcome is crucial in illustrating your problem-solving skills.

Outline your strategy for communication and setting clear goals at the project outset. Highlight the importance of regular updates and feedback loops to ensure that customer expectations align with project deliverables throughout the engagement.

Provide examples of projects where you've used Python or TypeScript to create integrations. Focus on the tools and libraries you utilized, the architecture of your solutions, and how your coding experience directly contributed to project success.

Discuss your approach to task management, possibly referencing tools or methodologies (such as Agile or Kanban) you use. Explain how you prioritize tasks based on urgency and customer requirements, and provide an example of past experience in this type of environment.

Share insights on best practices such as defining clear evaluation metrics, conducting regular assessments, and using A/B testing approaches. Discuss how to set up monitoring systems to continuously assess model performance in production environments.

Elaborate on how you follow industry news, take courses, or participate in webinars and meetups. Emphasizing your proactive approach towards continuous learning can show interviewers your commitment to professional growth in the AI field.

Express your enthusiasm for Braintrust’s mission in AI evaluation and how your skills align with the company's goals. Discuss the team culture and the opportunities for personal and professional growth that excite you about this position.