Embedded AI platform engineer

Job description

**job description:** Senior Embedded AI Platform Engineers to design, build, and scale AI agents and AI-powered developer tools that transform how embedded software is developed, tested, and shipped. Resource will work at the intersection of Generative AI, agentic AI systems, and embedded software engineering — building AI solutions that understand the complexity of multi-ECU architectures, real-time operating systems, safety-critical code, and industrial communication protocols. **Must have skills: Embedded C, RTOS, & C++ code understanding, Multi agent development hands on experience in Python; Orchestration experience** **What resource will Do** - Understand existing code based of Embedded Systems with RTOS - Design, build, and deploy multi-agent AI systems that automate software development workflows - Build context engineering frameworks that enable AI models to produce domain-specific, production-grade output for embedded software - Architect and implement RAG pipelines, knowledge graphs, and vector database solutions to give AI agents access to large-scale domain knowledge - Build enterprise integrations that connect AI agents with development tools (GitHub, Azure DevOps, CI/CD pipelines, test management systems) - Design automated quality gates and validation agents that ensure AI-generated output meets coding standards, safety compliance, and architecture guidelines - Build observability, metrics, and evaluation frameworks to measure AI impact on productivity, quality, and cost - Develop full-stack tooling (VS Code extensions, web dashboards, CLI tools) that deliver AI capabilities to engineering teams **What resource can Bring** - **Embedded Software Domain Understanding**           - Understanding of embedded software development workflows and toolchains           - Familiarity with C/C++ development for embedded systems           - Understanding of testing frameworks and methodologies: GTest, pytest, MIL, SIL, HIL           - Familiarity with real-time operating systems (RTOS) concepts           - Understanding of industrial communication protocols (CAN, J1939, Ethernet)           - Exposure to model-based software development (MATLAB/Simulink) is a plus           - Exposure to QT framework and UI development for embedded displays is a plus - GenAI & Agentic AI Expertise - Context engineering — designing and structuring domain context to maximize LLM output quality - Familiarity with AI-native development tools: GitHub Copilot, Cursor, Windsurf, Antigravity - LLM-based system architecture (OpenAI, Anthropic, open-source LLMs) - Multi-agent orchestration and tool-integrated agents - Retrieval-Augmented Generation (RAG) pipelines - Vector databases (Pinecone, Weaviate, ChromaDB, pgvector, or equivalent) - Agent frameworks (LangChain, LangGraph, CrewAI, AutoGen, or equivalent) - AWS Bedrock, SageMaker, and cloud-agnostic AI architectures - LLMOps, evaluation frameworks, observability, and guardrails - Prompt engineering, structured outputs, and function calling - AI governance, security, and responsible AI design - Custom & Offline AI Solutions           - On-premise and air-gapped LLM deployments           - Local and embedded AI agents for controlled environments           - Quantized models (GGUF, ONNX) and optimized inference pipelines - Local LLM orchestration using Ollama, llama.cpp, vLLM - Fine-tuning, domain adaptation, and hybrid AI architectures - Full-Stack Development           - TypeScript / JavaScript (Node.js)           - Python           - VS Code extension development or IDE tooling experience           - REST APIs, WebSocket, and modern web application frameworks           - Git, CI/CD pipelines, containerization (Docker, Kubernetes) **Preferred Qualifications** - 5+ years of software engineering experience - 2+ years of hands-on experience with LLM-based systems, generative AI, or agentic AI - Experience building AI solutions for engineering or developer productivity use cases - Experience in regulated or safety-critical industries (automotive, agriculture, aerospace, medical) is a strong plus - Bachelor's or Master's degree in Computer Science, Software Engineering, AI/ML, or related field