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

NXP SemiconductorsMunich, BavariaOn-siteFull-timeStaff, 8–12 yearsListed 2 months ago

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About this role

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

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