Solutions Engineering

Role Description

We're looking for a highly motivated Solutions Engineer to join our Solutions organization, reporting to the Head of Solutions Engineering. This is a customer-facing, hands-on builder role: you'll work directly with customers to scope, design, and deliver production solutions on top of the Archetype AI platform — from initial discovery through deployment.

You'll partner with Sales and Product on early customer engagements, then own the technical execution: building applications, integrations, and pipelines in real customer environments. This is a generalist role spanning the full stack, and we're especially interested in engineers who have shipped solutions end-to-end from edge devices to the cloud. Breadth and strong fundamentals matter more than any single specialty.

You should be comfortable in front of customers — translating requirements, walking through architectures, and presenting results — while also being the person who writes the code, deploys the system, and makes it work in production. You communicate clearly, document effectively, and take ownership from concept through deployment.

Core Responsibilities

• Partner directly with customers to understand requirements, scope solutions, and deliver production deployments across predictive maintenance, safety, and industrial IoT use cases.
• Lead technical discovery, architecture discussions, demos, and proof-of-concept builds with customers and prospects.
• Design and build full-stack applications and integrations that solve real customer problems, from prototype through production hand-off.
• Build and maintain backend services, APIs, and data flows that power real-time visualization and analytics in customer environments.
• Extend our plugin architecture (primarily backend, with frontend contributions as needed) following established design patterns.
• Implement protocol-level integrations: REST APIs, IoT connectivity (MQTT, OPC-UA, Modbus), streaming video (RTSP), and multi-sensor data flows.
• Contribute to edge-side software where needed: sensor ingestion, buffering, on-device processing, and reliable transmission to the cloud.
• Develop and manage data processing pipelines with messaging systems (Kafka, RabbitMQ, or similar).
• Support reliable delivery into customer environments through CI/CD, Kubernetes/Docker deployments, and infrastructure-as-code.
• Apply best engineering practices: testing, observability, versioning, and maintainability.
• Produce customer-facing technical documentation, runbooks, and internal templates that make successful deployments repeatable.

Qualifications

• 5+ years professional software engineering experience across client and server environments.
• Strong proficiency in TypeScript and Python, plus working proficiency in Rust or C++.
• Demonstrated experience designing and implementing scalable APIs, services, and integrations used by other engineers or applications.
• Experience developing within modular, plugin-based architectures with clear separation of concerns and well-defined interfaces.
• Experience with real-time or streaming data processing under latency and throughput constraints.
• Experience with Kafka or other messaging protocols and building data processing pipelines.
• Experience with communication protocols: REST APIs, IoT (MQTT, OPC-UA, Modbus), and video streaming (RTSP).

Preferred Qualifications

• Experience developing and deploying software on resource-constrained Linux devices, with familiarity with system-level concerns such as resource usage, process management, and I/O.
• Experience taking solutions end-to-end, all the way to edge device deployments and launching cloud services in production.
• Experience with CI/CD pipelines, Kubernetes/Docker deployments, and infrastructure-as-code.
• Familiarity with front-end frameworks (Svelte, React, Tailwind) and data visualization libraries (e.g., D3.js, Recharts, Plotly) for building customer-facing demos.
• Experience building frameworks, SDKs, or internal developer tools that scale across teams.
• Background in industrial IoT, predictive maintenance, or safety/security applications.
• Familiarity with real-time data visualization and applied AI/ML.