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Solution Engineers are highly skilled technical professionals possessing an in-depth understanding of Kubernetes, Linux, and Cloud systems. Their expertise extends to the Domino platform, which they leverage to guide and optimize the AI strategies of their customers. These engineers take a holistic approach to their work, recognizing that successful AI implementation goes beyond technical proficiency. They focus on people and processes, collaborating closely with customers to design and implement solutions that align with their unique business needs. This involves a wide range of activities, including the implementation, enhancement, integration, and customization of Domino deployments. By taking a customer-centric approach and focusing on delivering tangible business value, Solution Engineers play a critical role in ensuring the success of every customer engagement. They are not simply technical implementers, but rather, they are trusted advisors and value creators who help customers navigate the complexities of the AI landscape and achieve their business objectives.
Job Responsibility:
Build custom solutions for customers that integrate with Domino to enhance the customer experience. The solutions built should be well documented, tested, and the rest of the PS team should be enabled on the solution
Collaborate with the larger Domino team to ensure that the customer's voice is being heard with regards to feature or bug prioritization as well as feedback on the platform
Create reproducible artifacts that address recurring client needs, enhancing efficiency and consistency in our delivery process. These artifacts should follow best practices, be tested in various scenarios, and have thorough documentation
Regularly solicit feedback from customers regarding the quality, effectiveness, and relevance of solutions delivered. Use this feedback not only as a metric of personal success but also as a means to identify areas of improvement, ensuring that the solutions provided align perfectly with client needs and expectations
Requirements:
5-10+ years professional experience with customer facing technical role in pre-sales, professional services, consulting or customer success preferred
Strong customer-facing communication skills, including the ability to run structured discovery and clarify ambiguous requirements
Technical depth to scope solutions, ability to create production ready code (Python preferably)
Ability to script and prototype as needed, including comfort “vibe coding” to move quickly in technical workflows
Experience running or supporting benchmarks for ML inference deployments