Principal AI Engineer

Stellantis; Auburn Hills (MI); On-site; USD 180,000 - 280,000; Full time

Job summary

Stellantis is seeking a Principal AI Engineer to lead the design, development, and deployment of enterprise-grade AI-powered automation systems. The role emphasizes owning production-scale AI solutions and driving measurable improvements across the organization.

The ideal candidate will have 10+ years of software/AI experience, deep LLM expertise, strong Python skills, and a product mindset, with a track record of delivering impactful AI at scale.

Qualifications

• Bachelor's degree in AI, ML, CS, statistics, or related field.
• 8+ years of professional software/AI experience with hands-on work on LLM-based systems.
• Proven production experience with Large Language Models, including prompt engineering and model integration.
• Strong proficiency in Python and modern AI/ML frameworks such as PyTorch/TensorFlow.

Responsibilities

• Lead design, development, and deployment of LLM-based automation solutions across functions.
• Define problem statements, data requirements, system boundaries, and solution approaches.
• Architect and implement end-to-end LLM systems (prompt pipelines, agent-based architectures, RAG).
• Integrate commercial/open-source LLMs into enterprise systems and products.
• Drive model evaluation, prompt optimization, and reliability improvements.
• Establish monitoring, logging, and evaluation frameworks.

Skills

LLM expertise

Python

LangChain

Prompt engineering

System design

English communication

Education

Bachelor's degree in AI/CS

Master's degree (Preferred)

PhD (Preferred)

Tools

PyTorch

TensorFlow

LangChain

APIs

Job description

We are seeking a Principal AI Engineer with deep, hands-on experience in Large Language Models (LLMs) to lead the design, development, and deployment of enterprise-grade AI-powered automation systems across the organization.

This role goes beyond experimentation. You will own and deliver production-scale AI solutions, analyze complex internal workflows, identify high-value automation opportunities, and architect intelligent systems that materially improve efficiency, accuracy, and scalability.

This position is ideal for a seasoned engineer (10+ years) who combines strong technical depth, architectural judgment, and a product mindset, and who enjoys building practical, high-impact AI systems used at scale.

KEY RESPONSIBILITIES:

• Lead the design, development, and deployment of LLM-based automation solutions across multiple business functions.
• Work closely with cross-functional teams to define problem statements, data requirements, system boundaries, and solution approaches.
• Architect and implement end-to-end LLM systems, including:
  • Prompt pipelines
  • Agent-based architectures
  • Retrieval-Augmented Generation (RAG) systems
  • Internal AI services and APIs
• Integrate commercial and open-source LLMs (e.g., OpenAI, Anthropic, Databricks, open-source models) into enterprise systems and products.
• Drive model evaluation, prompt optimization, and system reliability improvements based on real-world usage.
• Establish and maintain monitoring, logging, and evaluation frameworks for LLM-driven applications.
• Partner with product, operations, security, and engineering teams to map workflows and identify high-ROI automation opportunities.
• Ensure all AI solutions meet enterprise standards for data privacy, security, compliance, and governance.
• Act as a technical mentor and thought leader, setting best practices for LLM engineering and applied AI.
• Stay current with advances in LLMs, agent frameworks, AI infrastructure, and applied research—and translate them into pragmatic solutions.

Basic Qualifications:

• Bachelor's degree in AI, Machine Learning, Computer Science, Statistics, or a related field
• A minimum of 8 years of professional experience in software engineering, AI, or machine learning, including a minimum of 3 years of significant hands-on work on LLM-based systems.
• Proven, production experience with Large Language Models, including:
  • Prompt engineering and prompt optimization
  • Model integration and orchestration
  • Evaluation and reliability tuning
• Strong proficiency in Python and modern AI/ML frameworks and libraries (e.g., PyTorch, TensorFlow, LangChain, similar ecosystems).
• Solid background in deep learning and applied machine learning.
• Strong analytical and mathematical foundation relevant to ML systems.
• Experience designing systems that balance performance, scalability, cost, and accuracy.
• Ability to communicate complex technical concepts clearly to technical and non-technical stakeholders.
• Strong written and spoken English.

Preferred Qualifications:

• Master's degree in AI, Machine Learning, Computer Science, Statistics, or a related field (or equivalent professional experience).
• PhD or additional advanced degree in AI, Machine Learning, Computer Science, Statistics, or related fields.
• Experience building meaningful visualizations and explaining model behavior and results.
• Background in data mining, analytics, or decision-support systems.
• Experience with regression, supervised and unsupervised learning, and applied ML in production contexts.
• Prior experience with automotive, IoT, or large-scale industrial data.
• Contributions to open-source projects or published technical work.
• Experience operating AI systems under enterprise governance, security, and compliance constraints.