IoT Systems Integration Engineering Lead

Your mission

Connect sensors, gateways, and cloud systems into one reliable data pipeline. Keep sensor data accurate and complete and improve integration reliability with every release. Move quickly from pilot to production and make decisions with partial information. Build a culture that tests early, fixes fast, ships with confidence, and grows a team that delivers on time.

What you will own

Systems integration. Design and deploy multi-protocol IoT integrations, including Zigbee, Z-Wave, Matter, Bluetooth, Wi-Fi, and LoRaWAN, from native sensors to cloud platforms. Build integration frameworks and APIs that bridge sensor networks, edge gateways, and cloud data platforms.

Data ingestion and pipelines. Build ingestion services for telemetry, events, status updates, and firmware metadata. Design schemas, data models, and transformation logic for sensor data pipelines.

Cloud and edge infrastructure. Manage cloud infrastructure and edge systems with infrastructure-as-code and deployment tooling. Implement CI/CD pipelines and deployment automation.

Quality assurance. Own end-to-end QA across firmware, tag provisioning, mobile apps, web applications, and cloud services. Write and maintain unit, integration, and end-to-end tests. Build automated frameworks that validate sensor integrations and data accuracy.

Production reliability. Investigate and resolve production issues across integrations, data pipelines, and cloud infrastructure. Improve reliability through retries, idempotency, monitoring, and error handling.

Lasting corrective action. Containing production issues fast. Find root causes and verify that fixes prevent recurrence.

Daily operating discipline. Run short, focused daily reviews of integration and pipeline progress. Assign actions with clear owners and deadlines, surface stalled work, and make blocker decisions the same day.

Team leadership. Lead by influence across the engineering stack. Set clear goals, priorities, and quality standards. Mentor engineers through design reviews and direct feedback on architecture and QA. Build the team through hiring, and help define technical standards.

Pilots and partners. Lead pilot programs and technical validation with partners and customers. Turn pilot results into production-ready integrations.

Measurable results. Own clear, tracked targets for the platform. Keep sensor data accurate and complete across integrations. Keep ingestion reliable, with no duplicate records. Reduce production incidents and the time to resolve them. Launch pilots on schedule and move them to production. Keep test coverage high and deployments frequent and safe.

How you lead

Bias for action. You move fast from problem to decision. You test small fixes quickly and know when a change needs deeper validation. You act with urgency and never skip data quality or security.

Extreme ownership. You own the integration outcome from sensor to cloud. When a partner or dependency blocks delivery, you engage the right people, communicate the impact, and drive a recovery plan.

Relentless follow-through. You define what "done" means before work begins. You verify results in pilots and production, not just in tests, and you close the loop on every issue.

High standards and direct communication. You explain tradeoffs in plain terms across hardware, firmware, apps, and cloud teams. You raise risks early and hold the team to a high bar on accuracy and reliability.

Hands-on presence. You work in the lab, on the gateway, and in the cloud console. You trace failures from end to end, and you teach your engineers to do the same.

What you bring

Experience in systems integration, deployment engineering, or IoT platform development.

Ability to lead technical teams while staying hands-on.

Deep experience with multi-protocol IoT ecosystems, with at least three of Zigbee, Z-Wave, Matter, Bluetooth, Wi-Fi, LoRaWAN, and cellular.

Strong background in data pipeline design, data lakes, and ETL processes.

Strong Python skills and hands-on experience with data integration frameworks.

Proven expertise in building end-to-end QA frameworks across firmware, mobile, web, and cloud.

Experience with AWS or a comparable cloud platform for IoT data ingestion and storage.

Strong automated testing skills, including unit, integration, and end-to-end testing.

Experience with Git, CI/CD, code review, and production deployment.

Clear communicator across hardware, firmware, app, and cloud teams.

Experience with Linux.

A degree in computer science, electrical engineering, computer engineering, or a related field, or equivalent practical experience.

A plus, but not required

Experience building cloud-connected IoT or device-management platforms, AWS IoT Core, IoT Jobs, Device Shadows, or fleet provisioning, firmware OTA updates and telemetry systems, time-series databases (InfluxDB, TimescaleDB) or stream processing, infrastructure-as-code tools (AWS CDK, Terraform), familiarity with embedded systems and wireless communications, a track record launching products from alpha through production pilots, experience in aerospace, satellite, industrial IoT, or mission-critical environments, and a background in security-focused systems and operational compliance.