NXGEN Technology AG
Website:
nxgen.io
Job details:
Company Description
NXGEN is a Switzerland-based technology company redefining how the security industry operates. Our platform brings video surveillance, alarms, AI, and IoT sensors into one unified system used by monitoring centers around the world.
We’re not just building software; we’re transforming an industry. Our technology enables operators to manage thousands of sites, automate workflows with AI, and dramatically increase operational efficiency without increasing headcount.
At NXGEN, we believe great technology is built by great teams. We foster a culture of performance, innovation, and ownership where people are encouraged to think boldly, move fast, and continuously improve.
As NXGEN continues to grow and expand, we are looking for a talented AI Integration Engineer to join our team and help build the next generation of our device integration platform.
Role Description
The AI Integration Engineer will design, build, and continuously improve an AI-driven engineering pipeline that enables NXGEN to rapidly integrate edge devices, cameras, NVRs, access-control systems, alarm panels, IoT devices, and other physical-security technologies into our platform.
The role combines AI agent development, software engineering, device/API integration, automation, CI/CD, and testing to create a highly automated Device Integration Factory.
The long-term goal is to transform traditional manual integrations into an agentic workflow where AI agents can analyze vendor documentation, generate integration code, build and deploy integrations in isolated environments, run automated tests, identify and fix failures, and prepare validated changes for engineering review.
The engineer will own the architecture, implementation, and continuous improvement of this platform while keeping human engineers as the final approval authority for production changes.
Responsibilities:
- Design and build an AI-powered Device Integration Factory capable of automating the integration of new vendors and devices
- Develop structured workflows using AI coding agents such as Claude Code, OpenAI Codex/ChatGPT, LLM APIs, and agent frameworks
- Build AI agents capable of analyzing vendor documentation, SDKs, APIs, protocols, and sample code and converting them into actionable integration plans
- Develop reusable integration templates for REST APIs, WebSockets, TCP, MQTT, HTTP webhooks, RTSP, ONVIF, SIA, SDK-based integrations, Node-RED, and event-driven architectures
- Build AI-assisted capability mapping between vendor-specific functionality and NXGEN’s standard platform capabilities
- Create automated, isolated sandbox environments for safely building and testing AI-generated integrations
- Develop automated testing frameworks covering connectivity, authentication, device management, events, alarms, video, controls, reliability, and failure recovery
- Enable AI-driven test-case generation based on API specifications, device documentation, requirements, and existing integration patterns
- Integrate the AI development workflow with Git, CI/CD, Docker, artifact repositories, automated testing, code quality checks, and security scanning
- Build mechanisms that allow AI agents to create branches, generate and modify code, run builds and tests, troubleshoot failures, and prepare pull requests for engineering review
- Build and maintain an integration knowledge base containing vendor APIs, device capabilities, protocols, previous implementations, test cases, known issues, and lessons learned
- Develop an Integration Planning Agent capable of automatically generating implementation plans for new devices and vendors
- Perform device and protocol analysis when documentation is incomplete, including analysis of SDKs, network traffic, HTTP/WebSocket communication, TCP, MQTT, RTSP, and device logs
- Implement human-in-the-loop controls that identify situations requiring engineering intervention and generate clear escalation packages with evidence and recommendations
- Build observability for the AI integration pipeline, tracking execution time, iterations, failures, human interventions, test pass rates, code acceptance, integration reuse, and AI/API consumption
- Ensure AI-generated code follows security, compliance, and engineering standards, including secure credential handling, sandboxing, dependency scanning, SAST, container scanning, and auditability
- Automate the generation of integration documentation, API mappings, capability matrices, test plans, test reports, troubleshooting guides, and release notes
- Continuously analyze completed integrations and improve reusable patterns, templates, agents, and automation to make every future integration faster and more reliable
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field, or equivalent practical experience
- Strong practical experience building software systems using LLM-based coding agents and AI automation
- Hands-on experience with Claude Code, OpenAI Codex/ChatGPT coding workflows, LLM APIs, or similar AI coding tools
- Strong programming skills in several of the following: Python, JavaScript/TypeScript, Node.js, C++, C#, or Go
- Strong understanding of APIs, integrations, and communication protocols including REST, WebSocket, TCP/IP, MQTT, HTTP, RTSP, ONVIF, JSON/XML, webhooks, and authentication mechanisms
- Experience with agent orchestration, tool calling, structured outputs, prompt engineering, RAG, knowledge retrieval, and AI evaluation
- Experience building automated software development, testing, or deployment workflows
- Strong understanding of unit testing, integration testing, API testing, end-to-end testing, and test automation
- Experience with Git and CI/CD workflows
- Good understanding of Docker, Linux, cloud environments, and infrastructure automation
- Strong problem-solving and debugging skills, with the ability to analyze complex technical issues and incomplete documentation
- Strong English communication skills and ability to work collaboratively with software engineering and product teams
Preferred Qualifications:
- Experience with AI agent frameworks such as LangGraph, Semantic Kernel, CrewAI, AutoGen, or OpenAI Agents SDK
- Experience with MCP (Model Context Protocol) and AI tool integration
- Experience with Kubernetes, AWS, container networking, and observability platforms
- Experience with mocking, simulation, network/protocol testing, and hardware-in-the-loop testing
- Experience building AI-powered developer tools or autonomous engineering workflows
- Experience with IoT, video surveillance, CCTV, NVR/DVR, access control, intrusion detection, industrial automation, edge computing, robotics, telecom, or embedded systems
- Experience integrating device SDKs and network-based protocols
- Experience working with physical-security or edge-device vendors such as Hikvision, Dahua, Axis, Milestone, Senstar, Teltonika, Adpro, Safire, or similar vendors
- Experience with device reverse engineering, protocol analysis, Wireshark, tcpdump, Postman, curl, or similar tools
- Experience with security scanning, secrets management, software supply-chain security, and secure AI development practices
If you are interested, please send your CV to: recruitment@nxgen.io
Click on Apply to know more.
