Software Engineer - Microservices

Delta Dental•Oakland, CA

7h•$80,500 - $174,300•Hybrid

About The Position

The Software Engineer – Microservices is a hybrid role combining hands-on microservices development and AI engineering, with shared ownership of build, deployment, production operations, and security remediation. The role contributes to a fast-paced, production-critical environment and uses AI-assisted development and operations tools to improve productivity. The engineer designs, develops, tests, and maintains secure, scalable, resilient microservices for consumer-facing applications. The position involves Java and Spring Boot development, RESTful APIs, SQL, cloud deployment, test-driven development, code review, monitoring, documentation, security remediation, and production support. The engineer also applies AI tools and automation across the software lifecycle, ensures AI-generated code meets organizational standards, and works with senior engineers and architects to assess emerging AI technologies and enterprise use cases.

Requirements

At least 2 years of experience with a bachelor's degree in Computer Science or an equivalent technical field; additional experience may be accepted in place of education or a degree.
Experience developing backend applications using Java, Spring Boot, REST APIs, microservices architecture, and SQL.
Experience designing and developing secure applications and products.
Experience developing, configuring, and deploying applications on Microsoft Azure or another cloud platform.
Ability to identify key issues and details and present understandable alternatives to technical and non-technical audiences.
Ability to create and maintain technical documentation supporting product testing, installation, operations, deployment, and maintenance.
Ability to effectively present data to facilitate understanding of findings.
Analytical and creative problem-solving skills for designing, developing, and testing systems.
Strong knowledge of current technology trends and design patterns, with the ability to apply them as needed.
Ability to interpret technology heatmaps and develop plans to remediate hardware or software approaching End of Life or End of Support.
Ability to adhere to organizational processes and procedures, including Scrum and design artifacts.
Knowledge of Agile development methodologies.
A lifelong-learning and process-improvement mindset.

Nice To Haves

Demonstrated productivity gains using AI-assisted development and operations tools such as GitHub Copilot, Claude, or other enterprise-approved AI tools.
Experience with monitoring, logging, alerting, and tracing tools such as Datadog.

Responsibilities

Contribute to an engineering team building and supporting products that address business use cases, system challenges, and operational problems.
Participate in architectural design, system analysis, and application software programming, including independent research and study when needed.
Design, develop, test, and maintain secure, scalable, and resilient microservices for consumer-facing applications.
Write production-ready Java code using Spring Boot and RESTful API design principles.
Practice test-driven development and participate in peer code reviews.
Use AI-assisted development tools and generative AI throughout the software development lifecycle to accelerate coding, testing, debugging, refactoring, documentation, and modernization.
Identify opportunities to use AI agents and automation to improve engineering productivity and operational efficiency.
Address security vulnerabilities, patching, upgrades, and hotfixes in a timely and compliant manner.
Instrument applications and infrastructure with monitoring, logging, alerting, and tracing tools such as Datadog.
Partner with senior engineers and architects to evaluate emerging AI technologies and identify appropriate enterprise use cases.
Ensure AI-generated code meets organizational standards for security, performance, maintainability, testing, and compliance.
Develop maintainable, scalable, responsive, and secure software using best-practice data structures, algorithms, design patterns, and frameworks.
Own software delivery end to end, including specifications, quality, release deployments, production monitoring, and production support.
Produce complete, simple, readable technical documentation and maintain a team culture of documenting work.
Test and ensure code quality in line with test-driven development and continuous delivery principles, using test automation frameworks where possible.