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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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