Title: Software Architect – Physical AI & Digital Twin Systems
Position Summary:
Siemens Energy Gas Services (GS) is seeking a Software Architect (Physical AI) to define the architecture for AI-enabled cyber-physical systems used in industrial and manufacturing environments. This role focuses on robotics, perception, simulation and Digital Twin, edge/cloud platforms, and real-time system integration to enable more autonomous, efficient, and scalable factory operations.
You will architect scalable, secure, and maintainable platforms spanning cloud, edge, and on-prem environments, with responsibility for integration patterns, APIs, non-functional requirements, and technical standards. The role includes designing systems that connect software platforms with industrial assets such as robots, PLCs, sensors, and telemetry pipelines.
Working across engineering, operations, and data teams, you will shape architectures that support perception-to-action pipelines, Sim2Real workflows, and long-term platform evolution. You will also guide technology choices, architecture governance, and implementation direction for reliable deployment of Physical AI solutions at scale.
How You’ll Make an Impact (key responsibilities of role)
- Design and standardize scalable architecture across Physical AI systems, including robotics, Digital Twin, simulation, and orchestration platforms.
- Define architecture principles, integration patterns, API standards, and non-functional requirements including scalability, reliability, performance, security, and observability.
- Architect end-to-end solutions for AI/ML and GenAI use cases, including data pipelines, model integration, and operational readiness across cloud, edge, and on-prem environments.
- Design microservices-based, event-driven, and distributed system architectures aligned with modern SDLC practices, particularly for latency-sensitive robotic applications.
- Architect integrations across robot controllers, PLCs, industrial IoT, sensors, and edge systems using fit-for-purpose interoperability patterns such as OPC UA, ROS, MQTT, or equivalent approaches.
- Define system interactions across perception, planning, and control layers, including telemetry, sensor fusion, and closed-loop operational workflows.
- Support simulation, Digital Twin, and Sim2Real workflows to improve validation, deployment readiness, and continuous operational feedback.
- Establish code quality, review practices, and performance standards, and define comprehensive testing strategies across APIs, workflows, integrations, and end-to-end system behavior.
- Validate vendor deliverables against architecture principles, SLAs, security requirements, and acceptance criteria.
- Define data and AI architecture, including pipelines, model lifecycle, governance, traceability, responsible AI usage, and MLOps or LLMOps practices where applicable.
- Implement security, compliance, and observability frameworks, and design for high availability, fault tolerance, resilience, and performance optimization in real-time systems.
- Collaborate across engineering, operations, and data teams, provide technical leadership and mentorship, and drive architectural decision-making aligned to business goals.
What You Bring (required qualification and skill sets)
- Bachelor’s or master’s degree in computer science, engineering, data science, or any related field, or equivalent practical experience.
- 5 to 8 years of experience in software architecture, system design, and enterprise application development, with a proven track record of delivering scalable and maintainable solutions.
- Strong expertise in API design, API management, and integration patterns, including REST, gRPC, and event-driven architecture.
- Hands-on experience with cloud platforms such as Azure, AWS, or GCP and building cloud-native applications using microservices, Docker, and Kubernetes.
- Solid understanding of distributed systems, event-driven architectures, and real-time data processing.
- Experience with CI/CD pipelines, DevOps practices, Agile or Scrum methodologies, and infrastructure as code.
- Proficiency in backend development using modern programming languages or frameworks such as .NET, Spring Boot, Go, or Python.
- Proven experience designing and scaling enterprise-grade platforms across cloud and hybrid environments with strong focus on performance, reliability, and security.
- Strong understanding of security architecture, including IAM, data protection, and secure API design.
Good-to-Have Qualifications
- Hands-on experience with Digital Twin technologies, simulation platforms such as NVIDIA Isaac or Gazebo, or Sim2Real workflows.
- Experience with robotics systems, IoT, edge computing, or industrial automation, including PLCs, OPC UA, ROS, or equivalent technologies.
- Knowledge of AI/ML and GenAI systems, including MLOps or LLMOps, RAG pipelines, or agent-based workflows.
- Experience with real-time systems, sensor data processing, telemetry pipelines, or streaming technologies such as Kafka, MQTT, or event buses.
- Experience designing high-availability, fault-tolerant, and latency-sensitive systems.
Key Attributes
- Strong problem solving mindset and ability to work with team members from different domains.
- Excellent communication skills and willingness to support others across the team.
- Hands‑on engineering mindset with focus on practical development & deployment.
- Ability to clearly communicate complex technical concepts to non‑experts.
- High ownership and accountability.
- Comfortable working across R&D, engineering, and service organizations.
