Full stack developer Jobs in Long Beach, CA

Salary: $128,000 - 168,000 per year

Requirements:

• 3–6 years of professional software engineering experience in a production environment, with a track record of owning and shipping real systems.
• Strong proficiency in one or more of the following languages: Python, Java, TypeScript, Go, or C#; depth in one area is valued more than breadth.
• Solid understanding of object-oriented programming, SOLID principles, design patterns, and long-term maintainable architecture.
• Confident working with relational databases such as PostgreSQL or MySQL, including schema design, indexing, query tuning, and transactions.
• Working knowledge of at least one NoSQL database, such as MongoDB, Redis, or DynamoDB.
• Experience designing and consuming RESTful APIs, including service contracts and integration documentation.
• Ability to write meaningful unit, integration, and end-to-end tests for genuine confidence in the code.
• Familiarity with at least one major cloud platform, Docker, CI/CD pipelines, and basic infrastructure practices.
• Strong Git workflow experience, including branching, pull requests, and code review practices.
• Active use of AI coding assistants in day-to-day development, with demonstrated productivity or quality gains.
• Experience building or integrating at least one LLM-powered feature or workflow in a real project, including exploratory or side-project work.
• Understanding of prompt design, few-shot examples, and how to obtain reliable, structured outputs from LLM APIs.
• Ability to critically evaluate AI-generated outputs, validate them, and know when not to trust them.
• Genuine curiosity about AI tooling and a proactive approach to experimenting with new methods.
• Preferred: experience with RAG pipelines or vector databases such as Pinecone, pgvector, or Weaviate.
• Preferred: familiarity with AI frameworks such as LangChain, LlamaIndex, or similar orchestration tools.
• Preferred: exposure to ML concepts such as embeddings, model evaluation, fine-tuning, and working with data science teams.
• Preferred: experience with observability and monitoring tools such as Datadog, Grafana, OpenTelemetry, or equivalent.
• Preferred: background in microservices architecture and event-driven systems such as Kafka or RabbitMQ.
• Preferred: knowledge of security best practices, including OWASP Top 10, authentication and authorization, and input validation.
• Preferred: experience with Agile or Scrum methods and tools such as Jira or Linear.
• Preferred: open-source contributions or a public portfolio demonstrating engineering work.

Responsibilities:

• Design, build, and maintain scalable, high-quality software systems and APIs that serve real users in production.
• Write clean, well-structured code with appropriate unit, integration, and end-to-end test coverage.
• Architect and improve relational and non-relational database schemas, queries, and data models for performance and reliability.
• Perform meaningful code reviews that strengthen team quality and share knowledge.
• Debug, profile, and resolve performance bottlenecks and production incidents with urgency and discipline.
• Contribute to technical architecture decisions by proposing solutions, weighing tradeoffs, and documenting outcomes.
• Participate actively in Agile ceremonies such as sprint planning, standups, retrospectives, and backlog refinement.
• Deploy AI solutions end to end, from identifying the use case to building and shipping LLM-powered features into products and internal workflows.
• Integrate LLM APIs and AI frameworks into product features where they create real user value, such as search, summarization, recommendations, intelligent automation, and decision support.
• Apply sound engineering judgment to evaluate, refine, and validate AI-generated outputs before production release.
• Use AI coding assistants as a daily productivity accelerator and share effective AI tool patterns and prompt strategies across the team.
• Stay current with the AI tooling landscape by evaluating new models, frameworks, and techniques and bringing back deployment-ready recommendations.
• Partner with Marketing, Customer Experience, Data Science, Merchandising, Warehouse Ops, Finance, Supply Chain, Product, and Security to understand requirements and deliver technical solutions.
• Translate technical concepts clearly for non-technical stakeholders through documentation, presentations, and live discussions.
• Present project outcomes and architecture decisions to senior leadership with confidence and clarity.
• Contribute to knowledge sharing by writing internal documentation, running team demos, and mentoring peers.

Technologies:

• AI
• Architect
• C#
• CI/CD
• Cloud
• Datadog
• Docker
• Fine-tuning
• Git
• Grafana
• Support
• JIRA
• Java
• Kafka
• LLM
• Marketing
• MongoDB
• MySQL
• NoSQL
• OWASP
• OpenTelemetry
• PostgreSQL
• Python
• RAG
• RabbitMQ
• Redis
• Security
• TypeScript
• microservices
• Airflow
• AWS
• ArgoCD
• Azure
• Claude Code
• Copilot
• Cursor
• DevOps
• GCP
• GitHub
• GraphQL
• Jenkins
• Kubernetes
• OOP
• OpenAPI
• Prometheus
• REST
• SQL
• Spark
• Swagger
• Terraform
• dbt
• gRPC
• Fullstack

More:

We are a fast-growing technology company building products used by hundreds of thousands of customers, supported by a supply chain across multiple distribution centers and a data platform processing millions of events each day. Engineering is a core driver of business outcomes, and we move quickly with a high bar for quality. We embrace AI as a practical multiplier to ship better software faster, while still valuing strong craftsmanship. Our culture emphasizes outcomes over activity, speed as a feature, radical candor, continuous learning, open collaboration, and blameless post-mortems. This is a visible, business-facing engineering role with broad cross-team interaction and an emphasis on deployment-first AI work. CarParts.com is an equal-opportunity employer.

last updated 41 week of 2026