Software Engineer IV - Sales Domain (Java / Google Cloud)

Genuine Parts Company•Birmingham, AL

13d•Onsite

About The Position

We are seeking a highly experienced Software Engineer IV to join our Sales Domain IT team. This role will lead the design, development, and modernization of scalable, cloud-native applications in a Google Cloud environment, with a strong emphasis on Java-based microservices (Spring Boot / Quarkus). In addition to core backend leadership, this role will help our domain team integrate and operationalize AI-enabled capabilities and generative AI tools being transitioned from an innovation team. The ideal candidate will bring strong Java expertise, practical exposure to Python-based services, and the ability to guide and upskill a development team in modern cloud and AI-integrated architectures. This position requires hands-on technical leadership, architectural ownership, and a passion for mentoring teams while delivering scalable enterprise solutions that support the full quote-to-invoice lifecycle.

Requirements

Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field preferred.
15+ years of professional software development experience (enterprise-scale systems).
5+ years designing and building cloud-native microservices.
Experience modernizing legacy systems into distributed cloud architectures.
Demonstrated experience serving as a technical leader or senior individual contributor.
Expert-level Java proficiency (modern Java versions, concurrency, streams, async patterns).
Strong experience with Spring Boot and/or Quarkus.
Deep understanding of: Microservices architecture, RESTful API design, Event-driven systems, Distributed system patterns
Experience with relational databases, JDBC, ORM frameworks.
Experience with NoSQL/document databases (MongoDB preferred).
Experience deploying and managing applications in Google Cloud Platform (preferred) or comparable cloud platforms.
Experience with containerization (Docker) and CI/CD pipelines.
Familiarity with Pub/Sub or Kafka-based messaging systems.
Strong Git-based workflow experience.
Working knowledge of Python and ability to understand, extend, or refactor Python-based services.
Experience integrating AI/ML services into enterprise applications.
Familiarity with: REST-based AI APIs, Model inference services, Prompt-based generative AI integrations, AI service orchestration patterns
Understanding of security, governance, and responsible AI considerations in enterprise systems.
Strong ability to translate complex technical concepts into actionable guidance for teams.
Proven experience mentoring and elevating engineering teams.
Comfortable operating in ambiguity and leading modernization efforts.
Strong communication and cross-functional collaboration skills.
Ability to influence architectural direction without direct supervisory authority.

Nice To Haves

Exposure to AI/ML or generative AI system integration in production environments is strongly preferred.
Familiarity with Google Cloud Platform services such as Google Pub/Sub and Kafka.
Experience with generative AI platforms or LLM-based application integration
Experience with Azure DevOps pipelines and Jira for agile project management.
Additional knowledge of MongoDB and cloud-native CI/CD pipelines.

Responsibilities

Lead the design, development, and deployment of cloud-native Java microservices using Spring Boot and/or Quarkus within Google Cloud Platform.
Architect scalable, reliable, and secure systems aligned to enterprise modernization strategy.
Drive integration of AI/ML and generative AI capabilities into existing sales domain applications.
Collaborate with innovation and data teams to operationalize AI solutions into production-grade systems.
Provide technical leadership across a portfolio of sales-related applications.
Guide architectural decisions around API design, event-driven systems, and distributed microservices.
Mentor and upskill developers in: Cloud-native design patterns, Microservices architecture, AI service integration, Python service interoperability
Conduct code reviews and promote high standards for maintainability, testability, and documentation.
Partner with Product Owners, Architects, DevOps, and QA to deliver high-quality solutions.
Champion CI/CD, DevSecOps, and modern SDLC best practices.
Help define standards for responsible and scalable AI adoption within the domain.