Job Principal Engineer – AI-Enabled Embedded Software; Multi GenAI Orchestration,Jobs München Bayern,Stellenangebote in Deutschland

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

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, Dev Ops, 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 tool chains 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:
  - Lang Chain, Auto Gen, 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 tool chains
Dev Ops, Atlassian & Toolchain Integration
- Integrate AI into CI/CD pipelines and Dev Ops ecosystems
- Orchestrate across:
  - Bitbucket pipelines
  - Build and test systems
  - Release workflows
- Enable AI‑assisted Dev Sec Ops 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:
- 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:
  Lang Chain, Auto Gen, CrewAI
- Experience with enterprise AI governance and approved tool chains (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)
  - Dev Ops, CI/CD, Infrastructure‑as‑Code
  - Distributed systems & AI pipelines
  - Cloud platforms:
    Azure / AWS
Embedded Systems Expertise
- Strong understanding of:
  - Embedded systems, RTOS, tool chains
  - ECU architectures & ASPICE
- Expertise in:
  - Safety‑critical, real‑time systems

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