Top Remote Python Jobs in San Diego, CA

Design, build, and operate internal developer platforms, CI/CD pipelines, developer environments, deployment workflows, and shared services. Create automation and custom tooling, prototype and productionize AI-assisted engineering workflows, strengthen cloud and container foundations (Kubernetes, IaC), instrument platforms with telemetry, and own platform projects end-to-end including rollout, adoption, and on-call.

Build and maintain scalable backend applications, serverless functions, microservices, data workflows, ETL pipelines, and cloud-native architectures using Python and AWS. Manage databases, APIs, batch jobs, and real-time integrations while optimizing performance, scalability, security, compliance, and cost. Collaborate with product, engineering, analytics, and data teams; contribute to architecture, CI/CD, infrastructure automation, development standards, and technical mentorship. Healthcare claims data experience is required.

Define and drive Payments technical strategy and architecture for rails, routing, and funds-flow systems. Lead large cross-team initiatives, ensure financial correctness, improve reliability and cost via observability, mentor senior engineers, and align stakeholders across product, risk, and regulatory teams.

Develop Canvas and Model-Driven Power Apps for web and mobile, automate workflows with Power Automate, and integrate data from Dataverse, SharePoint, SQL Server, and external APIs. Build Power BI dashboards, troubleshoot performance and bugs, manage security roles, gather requirements, train users, and maintain applications. The role also involves Power FX and optional pro-code development using JavaScript, HTML, CSS, or C#.

The Senior Software Engineer for the Treasury team will develop backend services for fund management, ensuring system reliability and leading projects in a fast-paced environment.

Design, administer, optimize, and govern an enterprise Databricks Lakehouse Platform. Responsibilities include managing workspaces, Unity Catalog, compute, workflows, data pipelines, security controls, observability, performance, cost optimization, CI/CD, infrastructure automation, disaster recovery, and platform upgrades. The role also supports audits, compliance, troubleshooting, documentation, technical standards, and mentorship while integrating Databricks with enterprise data, business intelligence, and AI/ML environments.

Build and scale Cresta’s no-code conversation intelligence platform across the frontend and backend. Responsibilities include creating visual workflow editors, backend services and APIs, data models, storage layers, and scalable systems using React, TypeScript, Python or Go, Postgres, ClickHouse, and Elasticsearch. Collaborate with product, design, and AI/ML teams to deliver intuitive experiences for non-technical users while improving performance, reliability, security, and maintainability.

Own quality engineering for high-throughput payment systems by architecting automated regression, performance, stress, and load testing. Build emulators for external payment systems, integrate quality gates into CI/CD pipelines, validate microservices, event-driven architectures, and databases, and use Prometheus and Grafana for observability. Apply AI-assisted testing, synthetic data generation, and edge-case analysis while mentoring engineers and preventing incidents through telemetry-driven testing and post-mortems.

Build and scale ML-optimized HPC infrastructure, manage Kubernetes-based GPU/TPU superclusters, optimize for AI/ML training, and mentor teams while innovating in ML infrastructure.

Build and maintain reliable, secure, scalable backend systems for Lithic’s product platform. Own projects end to end across API key management, reliability, audit logging, search, and API infrastructure. Improve system reliability, reduce technical debt, participate in on-call rotations, and lead team process improvements while collaborating asynchronously across time zones.

Build and operate highly scalable storage infrastructure supporting petabyte-scale imagery data. Responsibilities include developing backend services and APIs, managing object storage and metadata indexing, tuning Elasticsearch, improving disaster recovery, monitoring performance, responding to incidents, contributing to architecture and roadmaps, and advising engineers. The role requires strong production software engineering experience with Go or Python, cloud-native systems, relational and non-relational databases, and highly available services.

Lead and grow a backend/platform engineering team building API-driven systems and core services. Own technical direction, architecture, reliability, and integration with product, data science, and infrastructure. Hire and mentor engineers, contribute to code and architecture, support incident response, and ensure scalable, secure, production-ready backend APIs and platform tooling.

Own and operate low-latency network infrastructure for trading systems, including colocation connectivity, exchange feeds, L2/L3 topology, BGP and OSPF routing, PTP synchronization, firewall policies, automation, packet analysis, documentation, and incident response. The role involves designing infrastructure from scratch, managing vendors, building Python tooling, and participating in on-call support within a small network engineering team.

Build scalable full-stack applications integrating healthcare insights with browser-based and Windows EHR systems. Develop products using FHIR and HL7 interoperability standards, collaborate on technical roadmaps, and implement performant solutions. Mentor junior engineers, conduct code reviews, make technical decisions, and partner with engineering, product, and business stakeholders using Agile processes.

Build and scale Daymark Health’s cancer care platform across the stack. Responsibilities include developing secure infrastructure and core systems, collaborating with product, data, operations, and customers, integrating workflows, following HIPAA and SOC 2 controls, handling PHI securely, and using AI coding tools to accelerate development. The role requires contributing to technical strategy, improving user experience, and adapting quickly in a startup environment.

Build and operate the multi-tenant platform layer for a GPU cloud service. Responsibilities include Kubernetes-based orchestration, tenant isolation, platform APIs and tools, GPU cluster automation, infrastructure as code, reliability and observability partnerships, customer issue support, environment templates, rollout tooling, architecture reviews, and reducing operational toil.

Owns reliability, observability, and incident response for a GPUaaS platform. Defines SLOs, builds monitoring and alerting systems, leads major incidents and post-incident reviews, automates operational processes, maintains runbooks, manages on-call operations, coordinates with engineering teams, drives chaos testing, reports SLA performance, and mentors junior engineers.

Monitor GPUaaS infrastructure, triage alerts, execute runbooks, coordinate incident response, communicate with customers, manage maintenance windows, resolve Tier 1 tickets, and improve monitoring and operational procedures. The role provides 24/7 rotating coverage, including nights, weekends, and holidays, while maintaining shift handoffs and active-incident documentation.

Forward Deployed Engineer responsible for managing client relationships, supporting end-to-end data product implementations, ensuring data quality and adoption, and coordinating account and engineering teams. The role develops scalable data pipelines and product lines, applies SQL or Python and statistical methods, creates visualizations, documents code, trains employees, and drives customer value. Experience with data products, retail or consumer data, BI infrastructure, and alternative data sources is valuable.

Build and maintain cloud-native production platforms, automate infrastructure and deployment environments, and bridge application development with production teams. Responsibilities include validating implementations, independently solving technical problems, developing small components, estimating work, debugging systems, and promoting DevOps, DevSecOps, CI/CD, infrastructure-as-code, containerization, and security best practices. The role requires Kubernetes and cloud experience, programming and shell scripting knowledge, YAML proficiency, cross-functional collaboration, and U.S. citizenship.

Own the DevOps strategy, cloud infrastructure, platform engineering, CI/CD, GitOps, observability, reliability, security, and cost optimization across client engagements. Lead architecture and automation across AWS, Azure, and GCP; establish infrastructure and delivery standards; manage incident response and SLOs; advise clients; mentor engineers; support hiring; and drive continuous improvement using DORA metrics.

Lead modernization of complex SQL Server stored procedures and design AI-native data infrastructure. Responsibilities include domain-driven data architecture, event-driven patterns, vector databases, embedding pipelines, semantic models, knowledge graphs, RAG evaluation, multi-platform data solutions, governance, and AI-assisted database tooling. The role partners across engineering and AI/ML teams, establishes reference architectures, mentors engineers, and contributes to enterprise data standards.

Own customer outcomes from discovery through production deployment. Build decision systems using ontologies, reasoning, graph analytics, optimization, and machine learning over enterprise data. Write Python, SQL, and PyRel; debug unfamiliar systems; tune performance; harden deployments; document reusable solutions; and upstream platform improvements. Lead technical workshops and proofs of concept while partnering closely with customers, Product, and Engineering.

Own and evolve Argo Workflows and Argo Events, make major architectural decisions, and build Pipekit’s enterprise control-plane product. The role includes shaping the roadmap, shipping customer-focused features, engaging with open-source contributors and customers, participating in an on-call rotation, and speaking at cloud-native conferences. Candidates should have strong statically typed programming skills, Kubernetes expertise, production-systems experience, excellent written communication, and a self-directed, customer-focused approach.

Lead design and build of scalable AWS cloud-based backend services and APIs powering web and mobile customer experiences. Own end-to-end feature delivery, improve grading and authentication workflows for scale and reliability, leverage AI tools to accelerate development, and provide technical leadership and mentorship across teams.