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secure connectivity solutions · automotive semiconductors

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

MunichPosted 6 days ago
HardwareStaff+Full Time
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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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