deep, handson experience in Large Language Models (LLMs)
to lead the design, development, and deployment of
enterprisegrade AIpowered automation systems
across the organization.
This role goes beyond experimentation. You will
own and deliver productionscale AI solutions , analyze complex internal workflows, identify highvalue 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, highimpact AI systems used at scale .
KEY RESPONSIBILITIES:
Lead the
design, development, and deployment
of LLMbased automation solutions across multiple business functions.
Work closely with crossfunctional teams to
define problem statements, data requirements, system boundaries, and solution approaches .
Architect and implement
endtoend LLM systems , including:
Prompt pipelines
Agentbased architectures
RetrievalAugmented Generation (RAG) systems
Internal AI services and APIs
Integrate commercial and opensource LLMs (e.g., OpenAI, Anthropic, Databricks, opensource models) into
enterprise systems and products .
Drive
model evaluation, prompt optimization, and system reliability improvements
based on realworld usage.
Establish and maintain
monitoring, logging, and evaluation frameworks
for LLMdriven applications.
Partner with product, operations, security, and engineering teams to
map workflows and identify highROI 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 handson work on LLMbased 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 nontechnical 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 decisionsupport systems .
Experience with
regression, supervised and unsupervised learning , and applied ML in production contexts.
Prior experience with
automotive, IoT, or largescale industrial data .
Contributions to
opensource projects
or published technical work.
Experience operating AI systems under
enterprise governance, security, and compliance constraints .
We are seeking a
Principal AI Engineer
with
deep, handson experience in Large Language Models (LLMs)
to lead the design, development, and deployment of
enterprisegrade AIpowered automation systems
across the organization.
This role goes beyond experimentation. You will
own and deliver productionscale AI solutions , analyze complex internal workflows, identify highvalue 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, highimpact AI systems used at scale .
KEY RESPONSIBILITIES:
Lead the
design, development, and deployment
of LLMbased automation solutions across multiple business functions.
Work closely with crossfunctional teams to
define problem statements, data requirements, system boundaries, and solution approaches .
Architect and implement
endtoend LLM systems , including:
Prompt pipelines
Agentbased architectures
RetrievalAugmented Generation (RAG) systems
Internal AI services and APIs
Integrate commercial and opensource LLMs (e.g., OpenAI, Anthropic, Databricks, opensource models) into
enterprise systems and products .
Drive
model evaluation, prompt optimization, and system reliability improvements
based on realworld usage.
Establish and maintain
monitoring, logging, and evaluation frameworks
for LLMdriven applications.
Partner with product, operations, security, and engineering teams to
map workflows and identify highROI 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.
At Stellantis, we assess candidates based on qualifications, merit, and business needs. We welcome applications from all people without regard to sex, age, ethnicity, nationality, religion, sexual orientation, disability, or any characteristic protected by law. We believe that diverse teams reflect our identity as a global company, enabling us to better address the evolving needs of our customers and care for our future.