Senior Software Engineer - AI Platform

As a Senior Software Engineer - AI Platform at Intetics Inc., your main responsibilities will include leading the design and development of AI-powered applications and services, building and integrating AI pipelines, and implementing generative AI use cases to enhance product offerings. You'll collaborate with cross-functional teams to leverage AI for improved efficiency and contribute to strategic planning within the AI team.

To qualify for the Senior Software Engineer - AI Platform position at Intetics Inc., you should have at least 7 years of professional software development experience. Additionally, expertise in Python, Java, JavaScript/TypeScript, and familiarity with generative AI and large language models is crucial. Hands-on experience with technologies like LangChain, Ollama, and cloud platforms is also required.

Intetics Inc. is committed to the professional growth of their Senior Software Engineers by offering opportunities for training and development. With a focus on innovative technology, the company encourages team members to stay updated with the latest advancements in AI and ML, which can greatly enhance their skills and career trajectory.

As a Senior Software Engineer - AI Platform at Intetics Inc., you should be well-versed in Python and TypeScript, alongside experience with AI frameworks like LangChain and Ollama. Familiarity with AWS, Azure, or GCP, as well as vector databases, will also be advantageous for this role.

At Intetics Inc., the team culture for Senior Software Engineers is dynamic and growth-oriented. Collaboration is encouraged, fostering an environment where innovative ideas and solutions are welcomed. The company values a balanced work-life dynamic, offering ample paid time off and flexibility in work arrangements, such as the ability to work from home.

In your response, highlight specific projects where you implemented generative AI and LLMs. Discuss the tools you used, such as LangChain or Ollama, and provide examples of how these technologies improved user interactions or automated processes.

Discuss your design methodology, including aspects like user experience, functionality, and scalability. Emphasize collaboration with cross-functional teams to ensure that the final product meets both technical and user needs.

Share your experience with benchmarking techniques, such as using specific metrics to evaluate performance. Discuss your approaches to tuning models and optimizing performance through active monitoring and iteration.

Explain the resources you utilize, such as industry publications, online courses, and participation in AI communities or forums. Highlight your proactive approach to continuous learning and how you apply new insights in your projects.

Provide examples of AI pipelines you have built or integrated, emphasizing your experience with data handling and model fine-tuning. Share insights into how these pipelines have improved efficiency or project outcomes.

Tell a story about a specific project where AI led to a significant innovation or solution. Focus on your role in the process, the challenges faced, and the positive impact on the user experience.

Discuss your strategies for quality assurance, such as code reviews, automated testing, and adherence to development best practices. Highlight examples of how these practices have led to successful project outcomes.

Explain your understanding of RESTful principles and how you've applied them in AI applications. Provide examples of how effective API design has facilitated the integration of AI solutions with other systems.

Emphasize your communication and interpersonal skills. Provide examples of past collaborative experiences, detailing how you facilitated discussions, gathered diverse insights, and synthesized them into actionable plans.

Share your vision for how AI can create societal benefits. Discuss specific initiatives you've been involved in where AI made a positive impact, particularly in health, finance, or community services.