Embedded AI platform engineer

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 (Git

Hub, Azure Dev

Ops, 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: Git

Hub 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 (Lang

Chain, Lang

Graph, CrewAI, Auto

Gen, or equivalent)

• AWS Bedrock, Sage

Maker, 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

• Type

Script / Java

Script (Node.js)

• Python

• VS Code extension development or IDE tooling experience

• REST APIs, Web

Socket, 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