AI Data Automation Engineer

Albers Aerospace•Cincinnati, OH

3d•Hybrid

About The Position

The AI-Data Automation Engineer will build automation and AI capabilities in support of various engineering processes. Resource must be U.S. citizen and able to obtain a security clearance. The position is preferred to be on-site in Evandale, OH, but may be supported offsite with some travel. This is a technically focused role emphasizing software development, scripting, and systems integration and outcomes will include production-ready software tools, automated workflows, and comprehensive technical documentation. However, supporting engineering through development and adoption will also be key responsibilities. This position will be highly collaborative with daily interface with other Albers team members as well as engineers from our customer company. This is an on-site position embedded at our customer’s Evendale, OH facility. You will develop new data automation solutions, produce user documentation, and assist in developing and presenting user training. You will work closely with Model-Based Systems Engineers in the military jet engine design and manufacturing domain.

Requirements

Bachelor’s Degree in Computer Science, Computer/Electrical Engineering or related STEM discipline
Must be a U.S citizen. Must possess or be able to obtain a Secret security clearance
Strong capability in scripting and programming languages (Python, C++, Java, SQL, etc.)
Proficiency in Windows and Unix/Linux programming environments
Deep understanding of data concepts, data integration practices, APIs, and web services
Experience with AWS, containerization (Docker/Kubernetes), and cloud-based solutions
Knowledge of SDLC methodologies, CI/CD pipelines, and automated testing frameworks
Version control systems (Git) and collaborative development practices
Background in engineering capabilities and tools (PLM - Teamcenter, Systems Engineering - Cameo, CAD - NX, etc.) and their data structures and APIs
Understanding of digital engineering processes, particularly CAD workflows and engineering analysis
Ability to understand and map business processes, capture requirements, and scope technical solutions

Nice To Haves

Graduate Degree engineering in Computer Science, Computer/Electrical Engineering or related discipline
1-3 years of relevant work experience
Knowledge of AI/ML frameworks and tools for automation (TensorFlow, PyTorch, scikit-learn, etc.)
Experience with database design and optimization (SQL and NoSQL)
Familiarity with RESTful APIs, microservices architecture, and distributed systems
Understanding of DevOps practices and infrastructure as code
Proven ability to execute independently on development projects
Strong problem-solving abilities and analytical thinking
Effective communication skills for technical and non-technical audiences
Ability to work in cross-functional teams and collaborate with business stakeholders
Resilience and persistence in debugging and resolving technical challenges

Responsibilities

Design, develop, and deploy automation and AI tools using cutting-edge technologies in a fast-paced, agile environment
Write high-quality, maintainable code that meets standards and delivers desired functionality using Python, Java, C++, or other relevant languages
Build and test integration/automation tools, working with business teams to ensure functional requirements are met
Apply principles of SDLC, Lean/Agile methodologies, CI/CD, and testing techniques to establish robust development pipelines
Work with IA and DT teams as necessary to deploy tools in classified spaces
Integrate with engineering toolchains (Teamcenter, NX, Cameo, Ansys, etc.) through APIs and data structures
Develop data integration solutions, working with various data sources, databases, and APIs
Balance delivery speed, quality, and sustainability of tools to support business outcomes at business pace
Define multigenerational capability roadmaps supporting immediate impact and visionary enablement
Engage with business teams to understand key process workflows and identify automation opportunities
Document to-be workflows and define/prioritize integration and automation gaps
Create comprehensive technical documentation, code comments, and developer guides
Provide necessary training and support to business consumers and engineering teams