Top Remote Software Engineer Jobs in San Diego, CA

Leads an engineering team developing and operating secure integrations with third-party systems and an integrations marketplace. Responsibilities include technical direction, delivery planning, architecture, API and data synchronization design, authentication, reliability patterns, CI/CD pipelines, observability, production troubleshooting, partner coordination, and applying AI to integration development and support.

Build and operate WISEcode’s food data lakehouse using Python, SQL, DuckLake, S3 Parquet, Postgres, and Prefect. Responsibilities include source ingestion, entity resolution, pipeline consolidation, data enrichment, downstream connectors, data quality reporting, configuration discipline, and architectural documentation. The role requires designing and shipping production lakehouse or warehouse systems, managing scalable API-driven pipelines, and collaborating closely with engineers in a fully remote environment.

Leads Clever’s engineering organization and technical strategy, overseeing architecture, execution, production systems, organizational design, recruiting, and leadership development. The role remains technically hands-on through architecture and code reviews, debugging, production support, and direct contribution. It also drives AI-assisted engineering, modernization of legacy systems, engineering productivity, and close collaboration with Product and executive leadership.

Lead the technical vision and architecture for scalable, secure, high-performance distributed systems. Provide engineering leadership, mentorship, and architectural guidance while driving reliability, automation, CI/CD, security, performance optimization, and technical strategy. Investigate emerging technologies, oversee complex problem-solving, establish engineering standards, and collaborate with product and business stakeholders to align technology roadmaps with organizational goals.

Build and ship full-stack software for school administrators, substitute teachers, and marketplace operations. Own problems end to end, from defining requirements and making product decisions through implementation, automation, and measurement. Develop features, integrations, billing and administrative tools using React, JavaScript or TypeScript, REST APIs, SQL, and relational databases. Apply AI tools, LLM APIs, agents, and automation to replace manual workflows while collaborating directly with cross-functional teams.

Full‑stack product engineer role with backend emphasis: build scalable Node.js services, develop React + TypeScript UIs (React Router v7), design APIs (tRPC/OpenAPI), optimize PostgreSQL queries and data pipelines, improve observability and infrastructure, write well‑tested code, and contribute to architecture and engineering practices in a fintech product.

Leads hands-on architecture, development, and delivery of secure healthcare systems while mentoring engineers and establishing engineering standards. Drives Azure, microservices, DevSecOps, automated testing, AI-assisted development, and scalable solutions. Partners with product, clinical, cloud, and security stakeholders to translate business needs into technical direction and support WelbeHealth’s PACE model.

Develop and deploy life-saving technologies as a fullstack engineer, focusing on web applications for public safety, collaborating with various engineering disciplines and leveraging customer feedback.

Build and maintain full-stack features across core financial platforms using Python, Django, PostgreSQL, and modern JavaScript or TypeScript frameworks. Design scalable systems, implement front-end interfaces and back-end APIs, write automated tests, optimize performance, resolve bugs, participate in code reviews, collaborate cross-functionally, and guide junior engineers while using AI-assisted development tools.

Develops and supports Azure, Power Platform, Power BI, and Databricks solutions for enterprise reporting, analytics, and cloud modernization. Responsibilities include migrating legacy systems, designing dashboards and data products, analyzing complex datasets, defining data requirements, troubleshooting performance issues, and collaborating with data engineering, architecture, science, and stakeholder teams in an Agile environment.