Senior AI Software Engineer

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

• 3–6 years of professional software engineering experience in a production environment, with examples of systems personally owned and shipped.
• Strong proficiency in at least one of Python, Java, TypeScript, Go, or C#.
• Knowledge of object-oriented programming, SOLID principles, design patterns, and maintainable architectural decision-making.
• Experience with relational databases such as PostgreSQL or MySQL, including schema design, indexing, query optimization, and transactions, plus working knowledge of a NoSQL store such as MongoDB, Redis, or DynamoDB.
• Experience designing and consuming REST APIs and working with service contracts and integration documentation.
• Ability to write meaningful unit, integration, and end-to-end tests.
• Familiarity with at least one major cloud platform (AWS, GCP, or Azure), Docker, CI/CD, and basic infrastructure practices.
• Strong Git workflow, including branching, pull requests, and code review.
• Regular use of AI coding assistants, with examples of improved productivity or quality.
• Experience building or integrating an LLM-powered feature or workflow; exploratory or side-project experience is acceptable.
• Basic understanding of prompt design, few-shot examples, and obtaining reliable, structured outputs from LLM APIs.
• Ability to test and validate AI-generated output, apply sound engineering judgment, and recognize when AI results should not be trusted.
• Genuine interest in AI tooling and willingness to experiment with new approaches.
• Preferred: experience with RAG pipelines or vector databases, AI orchestration frameworks such as LangChain or LlamaIndex, ML concepts, observability tools, microservices or event-driven systems, security practices, Agile/Scrum, or an open-source contribution or public portfolio.

• Design, build, and maintain scalable, high-quality production software systems and APIs.
• Write clean, well-structured, maintainable code with appropriate unit, integration, and end-to-end test coverage.
• Design and optimize relational and non-relational database schemas, queries, and data models for performance and reliability.
• Conduct constructive code reviews that strengthen team quality and share knowledge.
• Debug and profile software, resolve performance bottlenecks, and address production issues with urgency and rigor.
• Contribute to architecture decisions by proposing solutions, evaluating tradeoffs, and documenting outcomes.
• Participate in sprint planning, standups, retrospectives, and backlog refinement.
• Identify suitable AI use cases and deploy end-to-end solutions, including LLM-powered product features and internal workflows.
• Integrate LLM APIs and AI frameworks into features such as search, summarization, recommendations, automation, and decision support when they deliver genuine user value.
• Evaluate and validate AI-generated outputs before production, taking responsibility for the final result.
• Use AI coding assistants in daily development and share effective tools, patterns, and prompting strategies with the team.
• Assess emerging models, frameworks, and techniques and recommend practical options for deployment.
• Work with business teams to understand requirements and deliver technical solutions.
• Explain technical concepts to non-technical stakeholders through documentation, presentations, and discussions; present project results and architecture decisions to senior leaders.
• Share knowledge through internal documentation and team demonstrations, and mentor peers.

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

More:

We are CarParts.com, a fast-growing technology company whose products serve hundreds of thousands of customers. Our supply chain spans multiple distribution centers, and our data platform processes millions of events daily. Engineering is central to our business outcomes, and we value speed, measurable results, candid feedback, continuous learning, and collaboration across teams. Engineers contribute to requirements, architecture, and roadmap decisions in fast-paced sprints, with asynchronous work and intentional live collaboration. This forward-deployed engineering role focuses on applying AI in products and business workflows while maintaining strong software craftsmanship; it does not require AI research or ML specialization. You will partner with teams across Marketing, Customer Experience, Data Science, Merchandising, Warehouse Operations, Finance, Supply Chain, Product, and Security. Our technology landscape includes Python, TypeScript, Java, Go, SQL, relational and NoSQL databases, cloud platforms, APIs, AI and LLM services, and modern development and observability tools. The position is full-time and onsite at our Long Beach, California headquarters; remote and hybrid arrangements are not available. We are an equal-opportunity employer, and role duties may evolve with business needs.

last updated 42 week of 2026