UPSD Lead AI Architect

UPS; Alpharetta (GA); Hybrid; USD 150,000 - 190,000; Full time

Job summary

UPS in Alpharetta, GA seeks a Lead AI Architect to design, develop, and deploy enterprise-scale AI solutions, including LLM-powered apps, RAG, and agentic workflows. The role requires collaboration with data scientists, engineers, and business stakeholders to meet organizational KPIs.

The candidate should have hands-on experience with LangChain, Hugging Face Transformers, Docker, Kubernetes, and cloud platforms (GCP Vertex AI, Azure ML). Strong communication is essential.

Qualifications

• 3+ years of experience in AI including deep learning, ML, and NLP.
• Production experience building and deploying LLM-powered applications, including prompting, RAG, evaluation.
• Hands-on with agentic frameworks: Hugging Face Transformers, LangChain, LlamaIndex, CrewAI, AutoGen.
• Strong Python skills with Pandas, PySpark, TensorFlow, XGBoost, and production-grade apps.
• Experience designing RESTful APIs and microservices.
• Experience with cloud ML platforms (GCP Vertex AI, Azure ML) and vector DBs (Pinecone, Weaviate, Milvus, FAISS).
• Knowledge of Docker, Kubernetes and web tech (React, Golang).
• Knowledge of LoRA/PEFT and prompt tuning.
• Familiarity with knowledge graphs and LLM integration.
• Excellent communication and ability to translate AI concepts to non-technical stakeholders.
• Bachelor's degree in CS/Math/Stats or related field.

Responsibilities

• Design, develop, and deploy production LLM-powered applications with prompt/context engineering and RAG.
• Integrate LLMs with knowledge graphs and multi-agent systems.
• Architect agentic workflows using LangChain, LlamaIndex, CrewAI, AutoGen, and Hugging Face Transformers.
• Build scalable RESTful APIs and microservices exposing AI capabilities.
• Design vector DB schemas and embeddings pipelines (Pinecone, Weaviate, Milvus, FAISS).
• Apply traditional AI methods including supervised/unsupervised learning and NLP.
• Develop and execute model evaluation frameworks for safety and performance.
• Apply parameter-efficient tuning (LoRA, PEFT) to foundation models.
• Leverage cloud ML platforms (GCP Vertex AI, Azure ML) and Docker/Kubernetes for deployment.
• Collaborate with data scientists, engineers, and business stakeholders to align with KPIs.
• Document architectures, integration patterns, and deployment strategies.

Skills

Python programming

Communication

Leadership

Cross-functional collaboration

Education

Bachelor's degree in Computer Science/Math/Statistics

Tools

Pandas

PySpark

TensorFlow

XGBoost

RESTful APIs

Docker

Kubernetes

LangChain

LlamaIndex

CrewAI

AutoGen

Hugging Face Transformers

Pinecone

Weaviate

Milvus

FAISS

Job description

Explore your next opportunity at a Fortune Global 500 organization. Envision innovative possibilities, experience our rewarding culture, and work with talented teams that help you become better every day. We know what it takes to lead UPS into tomorrow—people with a unique combination of skill + passion. If you have the qualities and drive to lead yourself or teams, there are roles ready to cultivate your skills and take you to the next level.

Job Description

Position Summary

We are seeking a Lead AI Architect to design, develop, and deploy enterprise-scale AI and Generative AI solutions. The ideal candidate will have expertise in LLM-powered applications, agentic AI, RAG architectures, traditional machine learning, and cloud-based AI platforms, while providing technical leadership across cross-functional teams.

Key Responsibilities

• Designs, develops, and deploys production LLM-powered applications incorporating prompt engineering, context engineering, Retrieval Augmented Generation (RAG), and agent orchestration frameworks.
• Integrates large language models with knowledge graphs and multi-agent systems to solve complex, multi-step business problems.
• Architects and implements agentic workflows using frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, and Hugging Face Transformers.
• Builds and maintains scalable RESTful APIs and microservices to expose AI capabilities across the organization.
• Designs vector database schemas and manages embeddings pipelines using platforms such as Pinecone, Weaviate, Milvus, or FAISS.
• Applies traditional AI methodologies including supervised and unsupervised learning, deep learning, and NLP techniques such as tokenization, named entity recognition, text classification, and sentiment analysis.
• Develops and executes model evaluation frameworks to assess output quality, safety, and performance of deployed AI systems.
• Applies parameter-efficient fine-tuning methods including prompt tuning, LoRA, and PEFT to adapt foundation models for domain-specific applications.
• Leverages cloud ML platforms (GCP Vertex AI, Azure ML) and containerization tools (Docker, Kubernetes) to operationalize and scale AI workloads.
• Collaborates with data scientists, engineers, and business stakeholders to gather requirements, define scope, and ensure AI solutions align with organizational KPIs and decision-making needs.
• Documents AI system architectures, integration patterns, and deployment strategies to support knowledge sharing and organizational learning.

Qualifications

• 3+ years of experience in traditional AI methodologies including deep learning, supervised and unsupervised learning, and NLP techniques (e.g., tokenization, named entity recognition, text classification, sentiment analysis).
• Production experience building and deploying LLM-powered applications, including prompting, context engineering, agent architectures, evaluation frameworks, RAG pipelines, and vector database integration.
• Hands-on experience with agentic frameworks: Hugging Face Transformers, LangChain, LlamaIndex, CrewAI, and AutoGen.
• Strong proficiency in Python with deep experience in Pandas, PySpark, TensorFlow, and XGBoost; experience building production-grade applications required.
• Extensive experience designing, developing, and deploying RESTful APIs and microservices.
• Experience with cloud ML platforms (GCP Vertex AI, Azure ML) and vector databases (Pinecone, Weaviate, Milvus, FAISS).
• Knowledge of containerization and orchestration tools (Docker, Kubernetes) and/or full-stack development experience (React, Golang).
• Knowledge of prompt tuning, fine-tuning, and parameter-efficient adaptation methods (LoRA, PEFT).
• Familiarity with knowledge graph construction and integration with LLM and multi-agent systems.
• Strong communication and storytelling skills with the ability to present complex AI concepts to non-technical stakeholders.
• Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field; international equivalent or equivalent job experience accepted.

This role is located in Alpharetta, GA with a hybrid work schedule. In office Monday- Thursday.

Employee Type

Permanent

UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.

Other Criteria

UPS is an equal opportunity employer. UPS does not discriminate on the basis of race/color/religion/sex/national origin/veteran/disability/age/sexual orientation/gender identity or any other characteristic protected by law.

Basic Qualifications

Must be a U.S. Citizen or National of the U.S., an alien lawfully admitted for permanent residence, or an alien authorized to work in the U.S. for this employer.