Staff Application Engineer - AI Enablement

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Staff Application Engineer – AI Enablement based in the United States.

Join a forward-thinking engineering team focused on improving enterprise applications, data quality, and digital transformation through modern technology solutions. In this remote role, you will contribute to the development and optimization of Product Lifecycle Management (PLM) and Master Data Management (MDM) platforms. You will work hands-on with data mapping, system integration, application configuration, and proof-of-concept development to solve complex technical challenges. Collaborating with experienced engineers, project leads, and business stakeholders, you will help translate requirements into reliable, scalable, and reusable solutions. You will also explore emerging technologies and contribute to service-oriented architectures that improve efficiency and support evolving business needs. This opportunity offers a chance to strengthen your technical expertise, collaborate across disciplines, and contribute to impactful enterprise engineering initiatives.

Accountabilities

• Data integration and quality: Execute data mapping, data movement, interface development, and validation activities to maintain data quality and accuracy across PLM and MDM platforms.
• Application engineering: Develop, configure, and test application components based on project requirements, ensuring alignment with established software development approaches and technical standards.
• Technical design and documentation: Participate in project discussions, analyze task-level requirements, document design decisions, and communicate technical issues or exceptions to senior team members.
• Proof-of-concept development: Build and test proof-of-concepts using established design patterns, contributing hands-on technical implementation and evaluating potential solutions.
• Reusable platform development: Support the creation of service-oriented software and data delivery components that can be reused across projects to improve scalability and consistency.
• Enterprise systems integration: Collaborate with business functions to resolve data-related challenges involving system integration, product structures, and enterprise application workflows.
• Architecture and governance: Follow enterprise architecture standards, domain governance requirements, and established development practices while identifying opportunities for improvement.
• Technology research: Evaluate tools, emerging technologies, and technical approaches relevant to application engineering, PLM, and enterprise data management.
• Vendor assessment: Support vendor evaluation activities within the PLM functional area by gathering technical information and contributing recommendations.
• Cross-functional collaboration: Build strong working relationships with peers, project leads, and business stakeholders, sharing best practices and helping improve team effectiveness.
• Project coordination: Work with project management to communicate task progress, identify risks, raise issues, and ensure assigned deliverables remain aligned with broader project objectives.

Requirements

• Education and professional experience: Bachelor’s degree from an accredited university or college with at least four years of professional experience, an associate degree with at least seven years of experience, or a high school diploma with at least nine years of experience. A minimum of three years of professional experience in application engineering is required. Military experience is considered equivalent to professional experience.
• Enterprise application expertise: Experience working with enterprise platforms, particularly Application Lifecycle Management (ALM) and Product Lifecycle Management (PLM) systems.
• Data management and integration: Understanding of data mapping, data movement, system interfaces, data validation, and techniques for maintaining data integrity across enterprise applications.
• Software engineering knowledge: Familiarity with application development, technical configuration, testing methodologies, and reusable software components.
• Modern technology exposure: Experience or exposure to microservices, Service-Oriented Architecture (SOA), big data technologies such as Hadoop, enterprise search platforms such as Elasticsearch or Solr, cloud technologies, and DevOps practic…