Senior Software Engineer
$150k - $170kDigital Realty
Job Description Senior Software Engineer - Industrial Automation, Embedded Systems, Machine Learning & Edge AI Location: Ashburn, VA | Dallas, TX | Chicago, IL | Santa Clara, CA | Austin, TX | San Francisco, CA | Seattle, WA | Denver, CO | Charlotte, NC | Boston, MA | New York, NY Your Role As a Senior Software Engineer, you will lead the design and development of advanced software platforms, embedded control systems, industrial automation solutions, and Edge AI applications that support Digital Realty's next-generation data center infrastructure. Working across operational technology (OT), embedded hardware, cloud platforms, machine learning, and intelligent automation environments, you will create scalable solutions that improve reliability, efficiency, predictive insights, and operational performance across critical infrastructure systems. This role is ideal for an engineer who combines strong software development skills with hands-on experience in PLCs, industrial controls, embedded firmware, edge computing, machine learning, and intelligent automation. You will help drive innovation in power, cooling, automation, predictive analytics, digital twins, and AI-enabled infrastructure technologies across Digital Realty's global operations. What You'll Do
- Design and develop industrial automation software, control systems, and embedded applications for critical facility infrastructure.
- Develop PLC programs, HMI interfaces, SCADA integrations, and industrial control solutions supporting cooling systems, power systems, building automation, and data center operations.
- Create machine learning and predictive analytics solutions for fault detection, predictive maintenance, energy optimization, anomaly detection, and operational intelligence.
- Develop and deploy Edge AI and machine learning solutions that enable real-time decision-making, anomaly detection, predictive maintenance, intelligent control, and operational optimization across industrial and facility systems.
- Architect and develop scalable software platforms, APIs, microservices, and edge computing applications utilizing modern software engineering practices.
- Develop firmware and real-time software for microcontrollers, embedded Linux devices, industrial gateways, sensors, and intelligent control systems.
- Design and implement closed-loop control algorithms, data acquisition systems, and edge analytics platforms.
- Integrate PLCs, embedded devices, Building Management Systems (BMS), SCADA platforms, and Industrial IoT systems with enterprise and cloud-based applications.
- Design and implement communication interfaces and industrial protocols including Modbus RTU/TCP, BACnet, OPC-UA, EtherNet/IP, Profinet, MQTT, CAN Bus, I²C, SPI, Ethernet, and serial communications.
- Collaborate with operations, facilities, and engineering teams to deploy automation, monitoring, and optimization solutions across global data center environments.
- Lead technical design reviews, mentor engineers, establish engineering standards, and evaluate emerging industrial automation, edge computing, and AI technologies.
- Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, Mechatronics, Robotics, or a related technical field. Master's degree preferred.
- 5+ years of experience developing production-grade software, embedded systems, industrial automation solutions, or control systems.
- Strong programming skills in C/C++, Python, Rust, Go, C#, and/or Java.
- Hands-on experience developing firmware for Embedded Linux, RTOS platforms, ARM-based processors, STM32, ESP32, NXP, or similar microcontroller architectures.
- Experience designing, programming, and troubleshooting PLC-based control systems using platforms such as Allen-Bradley/Rockwell, Siemens, Schneider Electric, or Automation Direct products.
- Experience with industrial automation technologies including SCADA systems, HMI development, Building Management Systems (BMS), Distributed Control Systems (DCS), and Industrial IoT platforms.
- Knowledge of industrial networking, fieldbus technologies, and OT cybersecurity principles.
- Experience applying machine learning techniques to industrial systems, predictive maintenance, process optimization, anomaly detection, forecasting, or sensor-based analytics.
- Experience developing and deploying machine learning or Edge AI solutions utilizing frameworks such as TensorFlow, PyTorch, ONNX, OpenCV, Scikit-learn, or similar technologies.
- Experience developing edge-computing architectures integrating operational technology with cloud services such as Azure (preferred), AWS, or GCP.
- Experience integrating operational technology (OT) systems with cloud platforms and AI-enabled services.
- Knowledge of data center infrastructure, HVAC systems, liquid cooling technologies, power systems, energy management, or mission-critical facilities is highly desirable.
- Knowledge of AI-assisted automation, digital twins, intelligent monitoring systems, and data-driven optimization techniques for industrial environments is highly desirable.
- Experience with digital twins, advanced controls, robotics, autonomous systems, reinforcement learning, computer vision, generative AI, AI-assisted industrial automation, or model-based engineering is a plus.
- Strong leadership, communication, and systems-engineering skills with the ability to drive projects from concept through deployment.
Vacancy posted 5 days ago
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