Software Engineer - Microservices

Delta Dental•Oakland, CA

10h

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 supports consumer-facing applications in a fast-paced, production-critical environment and uses AI-assisted development and operations tools to improve productivity. The engineer works with Java, Spring Boot, REST APIs, microservices architecture, SQL, and cloud technologies, emphasizing engineering quality, automation, security, and continuous improvement. The engineer contributes to application architecture, analysis, programming, testing, deployment, production support, and monitoring. The role includes using AI tools throughout the software development lifecycle, maintaining secure and resilient systems, addressing vulnerabilities and upgrades, documenting developed software, and ensuring AI-generated code meets organizational standards. The position also involves collaboration with senior engineers and architects to assess AI technologies and appropriate 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 lieu 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 present data effectively to facilitate understanding of findings.
Analytical and creative problem-solving skills for system design, development, and testing.
Strong knowledge of prevailing technology trends and design patterns, with the ability to apply them as needed.
Ability to interpret and analyze technology heatmaps and develop plans to remediate hardware or software nearing end of life or end of support.
Competence in following organizational processes and procedures, including Scrum and design artifacts.
Knowledge of Agile development methodologies.
Commitment to continuous learning and process improvement.

Responsibilities

Contribute to an engineering team building and supporting products that address business use cases and system or 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 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 appropriate enterprise use cases.
Ensure AI-generated code meets organizational standards for security, performance, maintainability, testing, and compliance.
Develop maintainable, scalable, responsive, secure, high-quality production software using appropriate data structures, algorithms, design patterns, and frameworks.
Own specifications, quality, release deployments, and production health monitoring from conception through delivery and production support.
Produce complete, clear, and readable technical documentation and promote 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 wherever possible.