Top Remote Python Jobs in San Diego, CA

The Senior HPA Architect will lead architecture for AI Factory environments, focusing on complex GPU infrastructure solutions and business outcomes, while mentoring team architects and engaging C-suite stakeholders.

Develop automated solutions for material handling, including software design, integration, testing, support, and project management, primarily in back-end development.

The Database Engineer designs, optimizes, and evolves MySQL databases in high-volume settings, ensuring performance and reliability while collaborating with engineering and analytics teams.

Design, build, and operate Planet's scalable object and metadata storage platform. Own backend services, Elasticsearch indexing, search, event notification, and disaster recovery. Measure performance, create alerts, be on call, drive system design and architecture, mentor engineers, and contribute to the technical roadmap for highly available, cloud-native data infrastructure.

The Site Reliability Engineer will manage infrastructure stability and scalability, lead cloud migrations, and optimize performance across systems while mentoring team members.

Design, deploy, and operate Kubernetes-based large-scale storage and data platforms. Build automation, tooling, telemetry, and observability. Troubleshoot distributed systems, support CI/CD and IaC, participate in on-call rotations, capacity planning, and launch readiness.

The Senior Data Engineer will design and develop data systems and pipelines, perform analyses, and collaborate with stakeholders to improve decision-making in healthcare.

As a Senior Platform Engineer, you will design, implement, and maintain data models and infrastructure while improving data quality and scalability. You'll collaborate across teams and mentor fellow engineers to enhance data usability and reliability.

Lead automation and optimization of Filevine's data platform: performance tune MSSQL/Postgres, optimize Snowflake, provision infrastructure with Terraform/AWS, run stateful containers on Kubernetes, integrate AI/LLM and MCP for operational automation, manage CI/CD, capacity planning, documentation, and serve in 24/7 on-call rotation.

As a Data Engineer, you will design, build, and maintain data pipelines and workflows, transforming raw data sources into clean, reliable data streams for healthcare clients.

Lead architecture and implementation of scalable, resilient insurance application systems across Life, Health, and Annuity. Drive technical strategy, design integrations, mentor engineers, evaluate vendors, and ensure reliable CI/CD, DevOps, and platform standards while collaborating with product, underwriting, and cross-functional teams.

As a Tech Specialist, you will bridge business ideas with digital tools, use AI for automation, troubleshoot issues, and assist the CTO while learning the tech department's operations.

Design, build, and operate backend platform services and infrastructure, owning features end-to-end from design through production. Improve reliability, performance, and scalability across services and the data layer, investigate and resolve production incidents, and convert fixes into durable improvements. Perform database work as needed (query/index tuning, sharding, capacity planning) and collaborate with SRE and application teams to meet zero-downtime SLAs. Mentor peers and raise engineering quality through reviews and best practices.

The VP of Software Engineering leads the engineering organization, driving software development, scaling teams, and ensuring compliance with standards while collaborating across functions to support product and customer success.

Lead a team of developers to design and deliver UiPath RPA and agentic solutions. Provide technical guidance, architect sustainable automations, mentor engineers, integrate systems via APIs, configure UiPath AI/LLM interfaces and document understanding, and drive customer adoption and advocacy.

The Senior Software Engineer will design, build, and maintain solutions for transit agencies, focusing on IoT devices and cloud services, ensuring reliable communication and device management.

The Senior Site Reliability Engineer at Juul Labs ensures operational stability and performance of hybrid cloud infrastructure, leads automation, and handles critical incidents.

Lead the bioinformatics pipeline team, setting technical strategy and architecture. Ensure engineering best practices, mentor staff, and oversee DevOps strategy for reliable software delivery in a regulated environment.

The role involves designing and developing enterprise-grade software solutions, integrating AI tools, collaborating with teams, and maintaining documentation while enhancing productivity for Yahoo personnel.

Design, scale, and operate secure AWS cloud infrastructure (EKS, IAM, RBAC); build and maintain IaC (Terraform/Terragrunt), GitHub Actions CI/CD, Datadog observability, and Python automation; document runbooks, participate in on-call rotations, postmortems, and Agile workflows to improve reliability and security.

As a Senior SDET, you will design and maintain test automation frameworks, embed with product teams to ensure quality, and implement AI-powered testing solutions.

Lead enterprise cloud strategy and architecture on Google Cloud, drive multi-cloud interoperability, enforce governance and security, optimize cost, deliver large-scale implementations (GKE, BigQuery, Vertex AI), mentor senior engineers, and promote GitOps and automation across the delivery lifecycle.

Own CI/CD, reliability, and deployment infrastructure for GTM systems (Salesforce, NetSuite, MuleSoft, Workato) and AI agent workloads on GCP and AWS. Build pipelines, observability, environment lifecycle, secrets management, IaC, container security, and runbooks. Partner with developers, Security, and IT to enforce guardrails, perform incident RCAs, and automate tooling to increase deployment safety and velocity.

The Principal Engineer will architect and develop scalable AI-driven data platforms, mentoring engineers and aligning technical strategies with business goals.

Design and build backend systems and APIs for AI-driven products, ensuring scalability, reliability, and integration of ML models while collaborating with engineering and product teams.