AI Solutions Engineer

Typically requires a University Degree and minimum 5 years prior relevant experience or an Advanced Degree in a related field and minimum 3 years of experience.
5+ years of progressive experience in software development
3+ years of hands-on development expertise
Demonstrated leadership or ability to technically mentor and inspire teams through complex projects.
Demonstrated ability to gather and analyze requirements, architecting comprehensive solutions across multiple domains (enterprise, application, data, integration, infrastructure, security)
Strong analytical skills and proactive problem-solving abilities, with a deep understanding of AI/ML technologies, cloud architecture, and enterprise software.
Exceptional written and verbal communication skills with the ability to articulate complex ideas clearly and effectively, including diagramming.
In-depth knowledge of web services, microservices architectures, and SOA
Proficiency in advanced software design paradigms and programming languages
Proficiency in cloud-native architectures and deep expertise in major cloud platforms (AWS, Azure, GCP)
Proficiency in DevOps methodologies, tools, and containerization technologies (e.g., Docker, Kubernetes, Jenkins)
Familiarity with AIOps concepts and tools with Hands-on experience with Infrastructure as Code (IaC) tools (e.g., Terraform, Ansible, AWS Sam Script) a plus
Experience with XR technologies (e.g., Unity/Unreal Engine, Quest/Vive/Hololens 2 development) a plus

Partner with multiple teams across the organization to ensure the seamless integration and successful delivery of solutions, adhering to SAFe’s collaborative ethos.
Articulate complex technical concepts clearly and concisely to both technical and non-technical audiences, fostering seamless collaboration across SAFe teams.
Design scalable digital solutions leveraging both external, internal, and newly developed capabilities.
DevOps methodologies, and AIOps strategies, championing containerization and Infrastructure as Code (IaC) best practices.
Proactively identify and mitigate technical risks associated with projects and initiatives, considering the broader implications within the SAFe context.
Develop integration strategies with existing enterprise systems.
Collaborate with AI engineers and business stakeholders.
Ensure solutions account for scalability, security, and compliance.
Enable efficient deployments of AI solutions by internal AI engineers.
Ensure solutions meets the needs of business users across the enterprise and costs are optimized.

Familiarity with AIOps concepts and tools with Hands-on experience with Infrastructure as Code (IaC) tools (e.g., Terraform, Ansible, AWS Sam Script) a plus
Experience with XR technologies (e.g., Unity/Unreal Engine, Quest/Vive/Hololens 2 development) a plus