Senior AI Engineer - Supply Chain Intelligence

Soltech•Alpharetta, GA

18h•Hybrid

About The Position

Our client is seeking a Senior AI Engineer to join its Platform and Innovation R&D team, helping design and build the next generation of Supply Chain Intelligence solutions. This is a hands-on engineering role for someone who is passionate about artificial intelligence, generative AI, and building production software with AI. You will contribute across the design and development lifecycle, working on AI-powered applications, data infrastructure, analytics, and scalable software solutions used by the company’s customers. The ideal candidate brings strong Python and AI engineering experience, solid software engineering fundamentals, and experience taking AI solutions beyond experimentation into real-world applications. You should be comfortable learning and working across technologies rather than being defined by a single programming language. You will collaborate closely with Engineering and Product Management in a fast-paced R&D environment where experimentation, adaptability, technical ownership, and communication are important. This position follows a hybrid schedule with 2–3 days per week in the Alpharetta, Georgia office. Candidates must currently reside in Georgia; relocation is not available for this position.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
5+ years of professional software engineering experience.
2+ years of experience working with AI/ML data infrastructure or developing AI/ML-enabled solutions.
Strong hands-on development experience with Python.
Demonstrated experience applying AI, machine learning, or generative AI technologies to software solutions.
Experience designing or supporting data infrastructure for model training, inference, and/or model monitoring.
Strong understanding of data modeling, ETL/ELT processes, and data governance.
Experience designing or developing real-time and batch data-processing pipelines at scale.
Familiarity with vector databases and embedding systems used in AI applications.
Experience with Docker, Kubernetes, microservices, and containerized application environments.
Strong software engineering fundamentals, including object-oriented design, architecture, design patterns, APIs, and scalable application development.
Experience contributing in a platform engineering and/or software architecture capacity.
Demonstrated use of AI coding tools as part of the software development process.
Ability and willingness to work across programming languages and technologies based on the needs of the solution.
Self-directed approach with the ability to take ownership and operate effectively in a fast-paced R&D environment.
Strong communication and collaboration skills.
Must currently reside in Georgia and be able to work onsite in Alpharetta 2–3 days per week.

Nice To Haves

Experience with Java, Spring, and/or Hibernate.
Experience developing SaaS or other high-volume, mission-critical software platforms.
Experience with RESTful and/or SOAP web services.
Web development experience with technologies such as JavaScript, Angular, HTML, CSS, XML, and JSON.
Experience developing AI capabilities within an enterprise software or SaaS product environment.
Experience with supply chain, logistics, ecommerce, or related technology platforms.

Responsibilities

Design and develop AI-powered applications and capabilities supporting the company’s Supply Chain Intelligence solutions.
Build and enhance generative AI and machine learning solutions for real-world customer and business use cases.
Design and develop the data infrastructure and pipelines required to support AI/ML model training, inference, and monitoring.
Develop scalable real-time and batch data-processing pipelines.
Work with vector databases, embeddings, and related AI technologies to support intelligent applications.
Apply strong data modeling, ETL/ELT, and data governance practices to AI and analytics solutions.
Design and develop scalable, mission-critical software within a SaaS environment.
Contribute to back-end business logic, workflows, integrations, messaging, and high-volume data processing.
Develop and integrate APIs and web services supporting AI-enabled and traditional application functionality.
Contribute to platform and software architecture decisions supporting scalable, maintainable solutions.
Build and support containerized, microservices-based applications using technologies such as Docker and Kubernetes.
Work across the technology stack as needed, including existing Java-based applications and web technologies.
Use AI-assisted development tools extensively as part of the software engineering process.
Collaborate with Engineering and Product Management to evaluate ideas, design solutions, and deliver new product capabilities.
Stay current with emerging AI technologies and identify practical opportunities to incorporate them into the platform.