Senior AI Engineer

As a Senior AI Engineer at Showpad, you will be responsible for designing, developing, and maintaining robust AI models to tackle complex business challenges. You will lead projects from initial scoping to final release, ensuring performance and reliability of our AI systems. Collaboration is crucial, as you will coordinate efforts across teams and mentor your colleagues, enhancing their technical skills and career growth. Additionally, you’ll craft and optimize prompts for our AI systems, contributing to the broader engineering strategy.

To qualify for the Senior AI Engineer position at Showpad, applicants need a strong educational background in Computer Science, Machine Learning, AI, or a related field. A minimum of 5 years' experience in developing and implementing AI models, along with solid knowledge of Python and hands-on experience with LLMs and AWS, is essential. Excellent problem-solving, communication, and collaboration skills are also key attributes for this role.

Senior AI Engineers at Showpad will work with state-of-the-art technologies such as LLM models (including LLama 3/3.1 and Claude models), and cloud platforms like AWS Bedrock, Sagemaker, and OpenSearch. Knowledge of programming languages such as Python, Typescript, and Kotlin is crucial as these are our primary tools for development in AI and machine learning projects.

Absolutely! Mentoring is a key aspect of the Senior AI Engineer role at Showpad. You will actively engage in driving the technical skills of both immediate and extended team members. This involves considering their career stages and personal goals, making the mentorship experience a fulfilling part of your job.

Showpad fosters a vibrant work culture focused on flexibility, trust, and setting individuals up for success. As a Senior AI Engineer, you'll be part of a collaborative environment that values every voice and promotes diversity and inclusion. The company supports personal development, offers opportunities for professional growth, and encourages team members to authentically express themselves while focusing on innovative approaches to challenges.

When addressing this question, provide specific examples of projects where you've used LLMs, detailing the models you worked with and the outcomes achieved. Highlight your familiarity with prompt engineering, and any innovative approaches you've applied in developing solutions. Emphasize your problem-solving skills and how they contributed to the success of the AI systems.

In your response, demonstrate your understanding of best practices in AI model development. Discuss methodologies you've implemented to test model performance, including validation techniques and continuous monitoring. Emphasize your proactive approach to identifying and addressing issues to maintain the reliability of AI systems.

Use this opportunity to showcase your leadership skills by outlining a specific project, the challenges you faced, and how you successfully guided your team through to completion. Focus on your role in project coordination and how you ensured collaboration among team members, while keeping the project aligned with business objectives.

Discuss your philosophy on mentorship and how you adapt your approach based on the individual's needs and career goals. Provide examples of mentorship experiences, focusing on how you helped mentees grow their technical skills and navigate their career paths effectively while creating an inclusive environment.

Explain your strategies for staying informed about the rapidly evolving AI landscape. This could include reading research papers, joining industry forums, attending conferences, or participating in online communities. Highlight your commitment to continuous learning and applying the latest technologies in your work.

Provide examples of specific AWS services you've integrated into your projects, detailing your experience with tools like AWS Sagemaker or Bedrock. Explain how these services contributed to the efficiency and performance of your AI solutions and any challenges you faced while leveraging cloud resources.

Talk about your approach to fostering communication and collaboration across teams. Share examples of successful cross-functional projects and how you ensured that all team members were aligned with the project goals, emphasizing your adaptability in working with diverse groups.

Outline a systematic approach for diagnosing and addressing performance issues. Discuss the importance of data analysis, retraining models, and possibly reevaluating your algorithms. Highlight your ability to learn from challenges and improve systems through iterative processes.

Share your passion for AI and machine learning, explaining what initially drew you to the field and what continues to inspire you. Highlight specific aspects of AI technology that excite you, such as its potential to solve real-world problems, create efficiencies, or innovate within the industry.

If you have experience with RAG systems, highlight the project details, your role, and the technologies used. Discuss the challenges you encountered and how they were overcome, emphasizing the impact of the system on overall project success.