Senior AI Engineer (Hybrid)

As a Senior AI Engineer at Nexxen, you will contribute significantly to the Gen AI team by guiding the development of conversational agents. Responsibilities include overseeing software project execution, facilitating team collaboration, and driving the implementation of innovative AI-driven solutions. You’ll work closely with developers, product managers, and business operations to ensure alignment on goals and project outcomes.

The Senior AI Engineer role at Nexxen requires a BSc in Computer Science or a related field, with a strong emphasis on 7+ years of experience in building customer-facing full-stack applications. You must have at least 2 years of hands-on experience with Python, proficiency in SQL and NoSQL databases, and a deep understanding of large language model concepts and usage.

Essential skills for a Senior AI Engineer at Nexxen include expertise in Python, a solid grasp of large language model core concepts, experience with Node.js (preferably Nest.js), and the ability to design agentic workflows. Familiarity with tools like Langchain or Langraph is an advantage but not a strict requirement.

Nexxen values the professional growth of its employees, offering opportunities to explore advanced AI technologies and participate in innovative projects. You will be part of a collaborative team that emphasizes a curious mindset and shares knowledge, effectively equipping you to take on new challenges and advance your skills in the field.

At Nexxen, the work environment is dynamic and fostering creativity. The company prides itself on a culture built around collaboration without ego and a customer-centric focus. As a Senior AI Engineer, you'll enjoy a hybrid work model that supports flexibility while being part of a passionate team committed to transforming advertising through technology.

When discussing your Python experience during the interview, highlight specific projects where you implemented AI-driven solutions. Discuss your familiarity with libraries like TensorFlow or PyTorch and how you've used Python for data manipulation, model training, or building web applications. This showcases both your technical skills and your practical application of Python in AI.

In preparation for this question, think about specific prompting techniques and reasoning strategies you've implemented. Discuss your experience with model fine-tuning, using transfer learning, and optimizing performance for specific tasks. Sharing successful outcomes from these strategies will illustrate your competence in handling large language models effectively.

To answer this, share your approach to task prioritization based on project deadlines, stakeholder needs, and team capabilities. Illustrate your method with examples of past projects where you’ve effectively balanced competing priorities while ensuring collaboration and transparency within the team. This demonstrates your ability to be organized and work well with others.

Addressing this question, emphasize your methodology for gathering customer feedback, understanding user needs, and iterating on AI solutions based on that insight. Discuss any relevant tools or techniques you’ve employed to measure customer satisfaction and improve the user experience, showcasing your commitment to a customer-focused approach.

When responding, detail your knowledge of agentic design principles and share specific instances where you created workflows that facilitated seamless interactions. Highlight any tools or frameworks you utilized and the impact these workflows had on outcomes, demonstrating your capability in designing efficient systems for conversational agents.

Prepare an example of a notable project where you successfully integrated AI functionalities using external APIs. Discuss the challenges faced, how you overcame them, and the eventual outcomes, allowing you to showcase both your problem-solving skills and technical savvy in API integration.

In your response, communicate your commitment to continuous learning. Mention resources like AI conferences, online courses, industry publications, or communities you engage with. This demonstrates your passion for the field and eagerness to apply new knowledge to your role at Nexxen.

Emphasize the importance of collaboration in AI engineering by discussing how cross-functional teamwork leads to more innovative, well-rounded solutions. Share examples where collaboration significantly improved project outcomes, highlighting your belief in the value of diverse perspectives.

When answering, stress the significance of open communication and the value of different viewpoints in technical discussions. Talk about your approach, such as facilitating a discussion to understand various perspectives and, if necessary, weighing decisions based on data and project goals, thereby showing your leadership and conflict resolution skills.

For this question, discuss specific metrics you believe are critical, such as accuracy, user engagement, or return on investment. Provide examples of how you have used these metrics to evaluate the success of previous AI projects, illustrating your analytical thinking and focus on results.