Solutions Engineering | Archetype AI Β· Teeming.ai
Archetype AI
Archetype AI helps businesses perceive and reason about physical environments using real-time sensor data to detect issues and automate responses. The company develops Newton, a proprietary Largeβ¦
Archetype AI helps businesses perceive and reason about physical environments using real-time sensor data to detect issues and automate responses. The company develops Newton, a proprietary Largeβ¦
What they do: Builds a Physical AI platform (Archetype Platform) and Newton, a multimodal foundation model for sensor/time-series fusion to enable edge-deployable Physical Agents.
Business model: B2B SaaS with API, agent toolkit, private fine-tuning, edge deployment, and GPU-accelerated inference for embedded AI.
Founded: 2023
Notable funding: $13M seed (Apr 2024) and $35M Series A (Nov 20, 2025)
Seed round announced tied to the Newton Physical AI model.
Series A- 2025-11-20
35000000
Series A announced on company blog; participation from multiple institutional investors.
Early seed (reported)- 2023-02-28
3100000
TechCrunch reported a $3.1M seed investment announced Feb 28, 2023 (closed earlier).
Investor Signal
βCompany lists participation from institutional and strategic investors including Venrock, Bezos Expeditions, Amazon Industrial Innovation Fund, Samsung Ventures, Gaingels, Plug and Play, Comcast NBCUniversal LIFT Labs, and others across rounds.β
Founders
What we do
Join the Team
Solutions Engineering
On-SiteSan Mateo, CA, US
On-Site β’ San Mateo, CA, US
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About Archetype AI
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 β 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 β translating requirements, walking through architectures, and presenting results β 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
Required 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.
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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.
