NXP Semiconductors
Principal Engineer – AI-Enabled Embedded Software (Multi GenAI Orchestration)
- Compensation
- Not disclosed
- Location
- Munich
- Work setup
- Not specified
- Seniority
- Principal
- Employment
- Not specified
- Experience
- Not specified
- Category
- Ai engineering
- Posted
Skills
Must have
- 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)
Full 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 ResponsibilitiesMulti‑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 deploymentAI-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