Principal Engineer – AI-Enabled Embedded Software (Multi GenAI Orchestration)

Darum lohnt es sich

Role Overview We are looking for a Principal Engineer / AI Architect to lead the transformation of embedded software engineering through AI‑first digitalization.

This role focuses on orchestrating multiple Generative AI systems (Multi‑GenAI) using NXP AI Community–approved tools, tightly integrated with the Atlassian platform (Jira, Confluence, Bitbucket) to enable autonomous, scalable, and intelligent software development ecosystems.

You will design and deliver AI‑driven SDLC platforms that combine agentic AI, GenAI, DevOps, and embedded engineering workflows—enabling self‑optimizing and highly automated development pipelines.

Key Responsibilities Multi‑GenAI Orchestration & Platform Architecture Define and lead architecture for Multi‑GenAI orchestration platforms leveraging NXP‑approved GenAI tools Design orchestration across: Multiple LLMs and AI services Agent‑based systems Engineering toolchains including Atlassian (Jira, Confluence, Bitbucket) Build modular orchestration layers for: Multi‑agent collaboration Cross‑model reasoning End‑to‑end workflow automation Ensure enterprise‑grade scalability, governance, and secure deployment AI‑Driven SDLC Transformation Architect and implement an AI‑enabled embedded SDLC Deeply integrate AI into: Jira (AI‑assisted backlog, requirements, traceability) Confluence (automated documentation & knowledge generation) Bitbucket (AI‑driven code workflows & reviews) Enable traceable, closed‑loop AI systems across requirements → development → validation Agentic AI & Autonomous Engineering Systems Design agentic AI systems for autonomous execution of engineering workflows Build multi‑agent orchestration frameworks using: LangChain, AutoGen, CrewAI Enable: AI‑driven code generation and optimization Automated debugging and root‑cause analysis Intelligent test creation linked to Jira workflows Implement self‑learning pipelines using feedback from developers and toolchains DevOps, Atlassian & Toolchain Integration Integrate AI into CI/CD pipelines and DevOps ecosystems Orchestrate across: Bitbucket pipelines Build and test systems Release workflows Enable AI‑assisted DevSecOps aligned with NXP AI governance Automate end‑to‑end developer workflows bridging Atlassian tools and AI systems Embedded Systems & ECU Integration Drive AI‑enabled transformation of embedded software development, including: Complex device driver development ECU software lifecycle (ASPICE aligned) Integrate AI into real‑time and resource‑constrained environments Ensure compliance with: MISRA ISO 26262 ISO/SAE 21434 Technical Leadership & AI Governance Champion NXP AI Community standards and approved GenAI tools Define best practices for: Multi‑GenAI orchestration AI integration with Atlassian ecosystem Drive adoption of an AI‑first engineering culture Lead cross‑functional innovation in AI‑enabled digital engineering platforms Required Skills & Qualifications AI & GenAI Expertise Strong experience with: Generative AI, LLMs, prompt engineering, RAG Multi‑GenAI orchestration & agent ecosystems Hands‑on with: LangChain, AutoGen, CrewAI Experience with enterprise AI governance and approved toolchains (NXP preferred) Software, Platform & Atlassian Expertise Strong programming skills: Python (AI/orchestration) C/C++ (embedded systems) Proven experience with: Atlassian platform: Jira, Confluence, Bitbucket (must‑have) DevOps, CI/CD, Infrastructure‑as‑Code Distributed systems & AI pipelines Cloud platforms: Azure / AWS Embedded Systems Expertise Strong understanding of: Embedded systems, RTOS, toolchains ECU architectures & ASPICE Expertise in: Safety‑critical, real‑time systems #J-18808-Ljbffr