IIoT Solutions Engineer

We are seeking an experienced Industrial IoT (IIoT) Engineer to design and build connected, data-driven industrial systems spanning the factory floor to enterprise cloud platforms. In this role you will architect end-to-end IIoT solutions, including edge data acquisition, secure connectivity, cloud ingestion, real-time analytics, and operational dashboards. The ideal candidate will combine strong software engineering skills with practical experience in industrial protocols, edge computing, and cloud IoT platforms. In this role you will work closely with cross-functional partners - product, design, engineering, operations, and business stakeholders - to translate ambiguous requirements into well-engineered solutions, and will be expected to raise the bar through code review, design review, and mentorship of more junior engineers. The successful candidate brings strong engineering discipline, a clear communication style, and a track record of shipping meaningful work that holds up well in production., * Architect end-to-end IIoT solutions spanning edge devices, gateways, connectivity, and cloud platforms.

• Design data acquisition pipelines from PLCs, SCADA, and sensors using protocols such as OPC UA, Modbus, MQTT, and Sparkplug B.
• Build edge computing applications using AWS IoT Greengrass, Azure IoT Edge, or similar platforms.
• Implement secure connectivity using mTLS, certificate management, and zero-trust patterns.
• Build cloud ingestion and processing pipelines using AWS IoT Core, Azure IoT Hub, Kafka, or similar.
• Develop real-time analytics, anomaly detection, and predictive maintenance models that turn raw telemetry from industrial assets into actionable signals for operators and reliability engineers.
• Build operational dashboards and alerts for plant managers and operators.
• Integrate IIoT data streams with MES, ERP, CMMS, and historian systems, designing reliable bidirectional flows that maintain consistency between operational technology and enterprise systems of record.
• Implement strong device management, including provisioning, OTA updates, and certificate rotation.
• Collaborate closely with OT, process engineering, and reliability teams, gathering requirements, aligning on technical approach, and ensuring that delivered solutions meet both functional needs and broader engineering and operational standards.
• Ensure compliance with relevant industrial cybersecurity standards (IEC 62443, NIST).
• Maintain comprehensive, current technical documentation - including architecture diagrams, design decisions, configuration references, runbooks, and operational procedures - so that the system remains supportable, auditable, and easy to onboard new engineers onto over time.
• Mentor and coach junior and mid-level engineers through code review, design review, pair programming, and structured knowledge sharing, helping the broader team grow in technical maturity and confidence over time.
• Continuously evaluate emerging IIoT technologies and platforms, assessing maturity, fit for purpose, and total cost of ownership, and make grounded recommendations on which to adopt, pilot, or defer based on real engineering needs., As an AI Engineer, you will play a pivotal role in shaping the future of AI systems by applying your domain expertise to train next-generation models. Your contributions will enhan…

• 15 days ago

• Bachelor's degree in Computer Science, Engineering, or a related technical discipline.
• Five or more years of IIoT or industrial software engineering experience.
• Strong programming skills in Python, C++, or Go.
• Hands-on experience with industrial protocols (OPC UA, Modbus, MQTT, Sparkplug B).
• Experience with at least one major cloud IoT platform (AWS, Azure, GCP).
• Hands-on experience with edge runtimes (Greengrass, IoT Edge).
• Solid understanding of OT/IT integration patterns.
• Experience with streaming and real-time analytics platforms.
• Familiarity with industrial cybersecurity standards.
• Excellent troubleshooting, communication, and documentation skills.

Preferred Qualifications

• Experience with digital-twin platforms.
• Hands-on experience with predictive maintenance ML models.
• Exposure to time-series databases (InfluxDB, TimescaleDB).
• Familiarity with Unified Namespace (UNS) patterns.
• Industrial certifications (ISA, IEC 62443).

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