Principal AI Engineer

Stellantis Financial Services; Auburn Hills (MI); On-site; USD 180,000 - 240,000; Full time

Job summary

Stellantis Financial Services seeks a Principal AI Engineer to own and deliver production-scale AI solutions across the organization. You will architect end-to-end LLM systems, integrate multiple models, and drive reliable, scalable automation across functions.

The role emphasizes hands-on leadership, deep technical depth, and a product-focused mindset to improve efficiency and governance while mentoring teams and shaping best practices.

Qualifications

• Bachelor's degree in AI, ML, CS, statistics, or related field
• 8+ years of professional experience in software engineering, AI, or ML with at least 3 years on LLM-based systems
• Production experience with Large Language Models including prompt engineering, integration, and evaluation
• Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, LangChain)
• Strong communication skills for technical and non-technical stakeholders
• Excellent written and spoken English

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 (prompts, agents, RAG, internal services)
• Integrate commercial and open-source LLMs into enterprise systems and products
• Drive model evaluation, prompt optimization, and reliability improvements
• Establish monitoring, logging, and evaluation frameworks for LLM apps
• Collaborate with product, operations, security, and engineering to map workflows
• Ensure AI solutions meet enterprise data privacy, security, and governance standards
• Act as a technical mentor and thought leader for LLM engineering
• Stay current with advances and translate into pragmatic solutions

Skills

LLM systems

Architectural judgment

Product mindset

Communication to stakeholders

Analytical thinking

Education

Bachelor's degree in AI/CS/ML/Statistics

Master's degree (preferred)

PhD or advanced degree (preferred)

Tools

Python

PyTorch

TensorFlow

LangChain

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.