Senior AI Engineer

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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:

Job Summary

This position provides input, support, and performs full systems life cycle management activities (e.g., analyses, technical requirements, design, coding, testing, implementation of systems and applications software, etc.). He/She participates in component and data architecture design, technology planning, and testing for Applications Development (AD) initiatives to meet business requirements. This position provides input to applications development project plans and integrations. He/She collaborates with teams and supports emerging technologies to ensure effective communication and achievement of objectives. This position provides knowledge and support for applications development, integration, and maintenance. He/She provides input to department and project teams on decisions supporting projects.

Position Overview

We are seeking an experienced Senior Tech Developer to solution and lead the development of next-generation AI/ML applications on Google Cloud. This role bridges machine learning, and DevOps, requiring expertise in cloud-native technologies and modern ML frameworks. You will take ownership of technical decisions, mentor engineering teams, and drive innovation across our platform.

Key Responsibilities

• Design and implement scalable AI/ML pipelines using Databricks and Python, optimizing for performance and cost
• Perform AI Engineering development, cloud-native solutions on Google Cloud, leveraging AlloyDB for data persistence and CloudRun for containerized services
• Build and optimize APIs using Google Cloud API Gateway, ensuring security, rate limiting, and monitoring
• Develop LLM applications leveraging Google's Gemini API for natural language understanding and generation
• Establish DevOps and artifact management practices using JFrog Artifactory for dependencies, build artifacts, and container images
• Lead technical design reviews and architectural decisions, providing technical guidance and mentorship to junior engineers
• Implement CI/CD pipelines with emphasis on build artifact management, versioning, and deployment automation
• Collaborate with cross-functional teams (Product, Data Science, Infrastructure) to deliver high-impact features

Required Qualifications

• 8+ years of software development experience with at least 3+ years in cloud-native architectures
• Advanced Python skills with demonstrated experience in production ML/AI systems
• Hands-on experience with Google Cloud Platform (GCP), specifically with AlloyDB, CloudRun, and API Gateway
• Proven expertise with Databricks for data engineering, feature engineering, and ML model training
• Strong understanding of LLM concepts and experience integrating or building applications with LLMs
• Experience with artifact repositories and build systems (JFrog Artifactory or equivalent)
• Expertise in microservices architecture, containerization (Docker/Kubernetes), and modern DevOps practices
• Demonstrated leadership skills with experience mentoring junior developers and driving technical excellence
• Strong problem-solving skills and ability to take ownership of complex, ambiguous challenges

• Employee Type:

Permanent

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

• 8+ years of software development experience with at least 3+ years in cloud-native architectures
• Advanced Python skills with demonstrated experience in production ML/AI systems
• Hands-on experience with Google Cloud Platform (GCP), specifically with AlloyDB, CloudRun, and API Gateway
• Proven expertise with Databricks for data engineering, feature engineering, and ML model training
• Strong understanding of LLM concepts and experience integrating or building applications with LLMs
• Experience with artifact repositories and build systems (JFrog Artifactory or equivalent)
• Expertise in microservices architecture, containerization (Docker/Kubernetes), and modern DevOps practices
• Demonstrated leadership skills with experience mentoring junior developers and driving technical excellence
• Strong problem-solving skills and ability to take ownership of complex, ambiguous challenges