Forward Deployed Engineer

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.

• 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.

• 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).

• 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.

• Startup or consulting experience

• 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.

• Open to stints of 1+ months of travel.