Intermediate Applications Developer

AI in this role

Design and implement scalable AI/ML pipelines, LLM applications, and cloud-native solutions on Google Cloud as a Senior Tech Developer.

geminidatabrickspythongoogle-cloudalloydbcloud-rungemini-apijfrog-artifactory

ai-engineeringdevopsmachine-learningllmcloud-nativeapi-design

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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.

How we rate this

Intermediate Applications Developer at UPS rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

AI EngineeringDevopsMachine LearningLLMCloud NativeAPI DesignGeminiDatabricks

Questions you could be asked

Tell me about a project where ai engineering was part of your work. What did you do?
Tell me about a project where devops was part of your work. What did you do?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where llm was part of your work. What did you do?
Tell me about a project where cloud native was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI Engineering, Devops, Machine Learning, LLM, and Cloud Native. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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