AI Senior Digital Engineer

This position is responsible for bridging the gap between central AI software and physical industrial automation infrastructure.

You are responsible for defining and harmonizing scalable system architectures that align with enterprise strategies and technology standards.

Your mission is to deliver adaptable, high-performance architectures by seamlessly blending cloud and edge-based AI models with physical Operational Technology (OT).

You contribute to architectural consistency across product lines, develop forward-looking system roadmaps, and define strict requirements that ensure data reliability, edge scalability, and robust cybersecurity.

Acting as the primary technical interface between Data Science teams and business units, you manage relationships with external system integrators to validate predictive analytics, drive innovation, and optimize energy efficiency.

What Will You Do?

AI Deployment & Infrastructure Integration


* Integration Architecture: Define, maintain, and execute the integration architecture between Edge System Management, AI Hub services, and existing physical equipment.


* Pipeline Interoperability: Design and optimize end-to-end data pipelines ensuring seamless data flow between legacy hardware and modern cloud/edge AI environments.


* Model Lifecycle Management: Build and maintain scalable systems for containerized AI model distribution, runtime integration, and live deployment at the edge.

Technical System Architecture


* Target Architecture: Define and communicate the architectural frameworks, ensuring strict technical consistency across existing platform infrastructure.


* Data Schema Design: Translate technical requirements into low-level integration designs, covering API contracts, system interfaces, data schemas, and integration patterns.


* Architectural Governance: Drive core technical decisions and ensure strict alignment on tech stacks across distributed engineering teams.

Engineering Leadership & Troubleshooting


* Hands-on Guidance: Provide deep technical support to development teams through strict code/design reviews, technical guidance, and problem-solving.


* System Integration: Systematically diagnose and resolve engineering mismatches, integration bottlenecks, and connectivity friction between cloud software and hardware.


* Validation & Testing: Lead structural validation, edge scalability testing, and end-to-end system behavior checks across all integrated components.

Technical Collaboration & Best Practices


* Cross-Team Engineering: Act as the primary technical bridge between Data Science/AI teams, Edge Architecture groups, and core Engineering.


* Standards Enforcement: Drive the adoption of strict engineering best practices regarding scalability, observability, performance, data reliability, and cybersecurity.


* Tech Exploration: Conduct targeted Proof of Concepts (PoCs) specifically focused on validating new integration paths, orchestration...