Third-Party AI Integration Engineer
(Edge-to-Cloud IoT/AI Specialist)
Job Summary:
We are seeking a technically strong AI Integration Engineer to design and operationalize secure, governed telemetry and control flows from edge gateways to external AI/LLM services. This role ensures edge-originating data is standardized and modular, conforms to API governance principles, and integrates seamlessly with both public-facing and internal platform APIs. You will also develop APIs to close the loop—allowing AI-generated control signals to influence device behavior in real time.
Key Responsibilities:
- Design Modular Edge-to-AI Pipelines:
Build real-time telemetry pipelines from edge gateways to AI inference endpoints, following schema-driven principles and aligning with internal API governance standards. - Normalize and Preprocess at the Edge:
Transform raw edge telemetry into standardized, structured formats compliant with OpenAPI or schema-driven contracts before forwarding to third-party LLMs. - Develop Bidirectional APIs for AI Interaction:
Build and expose RESTful or MQTT-based APIs for consuming AI responses and triggering feedback control actions within edge or gateway runtime environments. - Ensure Governance Alignment and Flow Integration:
Collaborate with firmware, backend, and AI/cloud teams to ensure data security (TLS/mTLS/OAuth2), validation, access control, and conformance with established governance models (as illustrated in the API Flow architecture). - Documentation and Developer Portal Readiness:
Author API specs, data models, and integration documentation to be published in the developer portal, supporting the modular, product-specific API subset approach.
Required Qualifications:
- Education:
Bachelor’s or Master’s degree in Computer Engineering, Software Engineering, or a closely related field. - Experience:
- Minimum 5-8 years integrating IoT edge telemetry with cloud platforms or AI services.
- Demonstrated implementation of schema-driven API flows and modular data exchange patterns.
- Technical Competencies:
- Fluent in API Integration - REST and MQTT protocols, Async with secure implementation using TLS, mTLS, and OAuth2.
- Practical experience integrating third-party LLMs or AI APIs (e.g., OpenAI, Google Gemini, Azure OpenAI).
- Strong coding skills in Python, Java, especially for embedded-edge or gateway environments.
Preferred Skills:
- Familiarity with API gateways (e.g., Kong), data model validation (JSON Schema), and schema-first API design.
- Knowledge of industrial telemetry protocols (e.g., OPC-UA, Modbus), and edge runtimes (e.g., Azure IoT Edge, EdgeX).
- Experience with OpenAPI/Swagger-based documentation and API lifecycle governance tooling.
Work Environment & Collaboration:
This position is embedded in a cross-functional engineering team operating at the convergence of firmware, AI/ML, and cloud architecture. The candidate is expected to work across product layers (device, gateway, platform) while adhering to the structured API flow and modular integration principles defined by the API Matters charter.
TIME TRAVEL REQUIRED
- 25%