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, 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

More information about NXP in Germany...