Software Engineer II

Job Description

We are looking for a Software Engineer II to join one of our Scrum teams building AI-native, event-driven services for automotive retail intelligence. This is a core contributor role for engineers with 2–4 years of experience who are ready to take end-to-end ownership of features, grow their distributed systems skills, and work in a high velocity environment that demands code quality, hexagonal architecture discipline, and genuine curiosity about AI-native engineering.

Key Responsibilities

• Develop and maintain Java (Spring Boot 3.x) backend services — implementing domain logic, REST APIs, Kafka event consumers/producers, and MongoDB/PostgreSQL persistence adapters following hexagonal architecture patterns.

• Build features across the full backend slice: domain model, port interface, adapter implementation, unit tests, and integration tests.

• Write integration tests using Testcontainers for MongoDB, PostgreSQL, Kafka, and Elasticsearch adapters — ensuring each adapter is tested independently from the domain core.

• Participate in design discussions, architecture reviews, and code reviews — actively learning from Staff and Senior engineers.

• Investigate and resolve bugs, performance issues, and Kafka consumer lag across services.

• Write clean, well-documented, testable code with consistent application of hexagonal design principles.

• Contribute to golden dataset test scenario design under the guidance of the Product Manager and SDET.

• Operate with ownership and curiosity in a fast-paced, startup environment.

Skills and Experience

• 2–4 years of backend engineering experience; Bachelor's or Master's degree in Computer Science or a related field.

• Solid Java fundamentals: object-oriented design, Spring Boot, REST API implementation, and unit testing (JUnit 5).

• Working knowledge of at least one of: MongoDB, PostgreSQL, or Kafka — with willingness to develop depth across all three.

• Understanding of hexagonal architecture concepts (ports & adapters) — ability to implement adapters under the guidance of senior engineers.

• Familiarity with cloud environments (AWS), containerization (Docker), and CI/CD pipelines.

• Strong problem-solving skills, attention to code quality, and ability to receive and apply feedback quickly.

• Collaborative mindset and clear communication — comfortable asking questions and flagging blockers early.

Preferred Skills

• Exposure to Kafka producers and consumers in a production or learning context.

• Familiarity with Elasticsearch for search and analytics use cases.

• Curiosity about AI/ML systems — awareness of what scoring models, embeddings, and LLMs do at a systems level.

• Exposure to Redis or Aerospike for caching patterns.
  
  

Perks and Benefits

• Competitive compensation and generous stock options.

• Medical insurance coverage.

• Work with some of the brightest minds from Silicon Valley's most dominant and successful companies.