Principal Engineer – AI-Enabled Embedded Software (Multi GenAI Orchestration)
Job Listings
·1 week ago
- Location
- Munich, Germany
- Type
- Full-time
- Department
- Engineering
- Seniority
- Lead
- Source
- Workday
Description
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
