Top Remote Python Jobs in Houston, TX

The Senior Software Developer II - Full Stack will design and develop scalable systems, leading projects while mentoring junior staff and engaging with stakeholders. The role emphasizes technical leadership, problem-solving in software development, and innovative processes in cloud and AI technologies.

The Backend Engineer will design, build, and scale Veda's backend systems, ensuring reliability and performance for DeFi applications.

Lead platform and infrastructure engineering to improve stability, developer productivity, CI/CD, observability, and shared libraries. Deliver platform projects, mentor engineers, own production availability and on-call, and drive platform decisions and best practices across the org.

Design, develop, and deliver fullstack web solutions, optimize platforms, mentor engineers, and manage product features from ideation to launch.

As a Staff Machine Learning Engineer, you will develop, productionize, and deploy ML models for clinical use, ensuring real-world effectiveness through hands-on coding and infrastructure building.

As a Software Engineer in Reliability, you'll architect and manage multi-cloud GPU infrastructure, ensuring performance, security, and scale while debugging complex hardware/software issues.

Serve as an embedded Linux expert on customer projects: design and refactor real-time architectures, develop Linux kernel drivers, debug low-level hardware/software issues, optimize kernel performance, collaborate with customers and internal teams, lead technical efforts, produce high-quality deliverables, and create technical proposals to support product lifecycle and certification.

The Software Engineer will build features across the stack, design AI/LLM-driven workflows, translate requirements, and collaborate closely with the founding team and customers.

Lead a cross-functional engineering team to design and deliver SMART on FHIR applications embedded in EMR workflows. Champion AI-driven, agent-assisted development, collaborate with data engineering on Python/dbt/SQL pipelines, implement engineering best practices, and manage hiring, mentorship, and stakeholder communication while ensuring quality, reliability, and interoperability.

The Senior Full-Stack Software Engineer will design, build, and scale backend services and APIs for financial transactions while collaborating with frontend engineers and contributing to technical design.

Develop and ship backend and frontend features that improve school-family communication. Collaborate with product and design, champion AI/LLM-driven workflows, build scalable secure services on AWS, evolve monolithic systems, participate in code reviews, and help shape architecture.

Design, build, and operate scalable AWS-based platform infrastructure for data processing. Improve pipeline automation, monitoring, security, and reliability. Lead CI/CD, IaC (Terraform/Scalr), network design, and incident response; collaborate with cross-functional teams and participate in on-call rotation. Integrate AI tools to streamline development and troubleshooting.

Define and drive full-stack architecture and technical vision across teams, write high-quality production code, lead zero-to-one projects, productionize ML systems, own reliability and SLOs, mentor senior engineers, and align engineering roadmaps with product and company strategy.

Design, develop, and document Salesforce solutions (Apex, LWC, Visualforce) and integrations; lead small developer teams; build APIs, data migrations, and test plans; ensure code quality and mentor others while evaluating and adopting AI-enabled tools.

The Senior DevOps Engineer will build secure, scalable infrastructure on AWS, manage Kubernetes platforms, and oversee FedRAMP-related tasks while ensuring compliance and operational efficiency.

Manage a team of cloud engineers to govern and optimize a multi-cloud environment while implementing security frameworks and managing vendor relationships.

The Site Reliability Engineer will lead technical initiatives, architect solutions, troubleshoot issues, mentor team members, and improve observability practices.

The Cloud Administrator manages cloud infrastructure and services, ensuring their performance, security, and reliability while troubleshooting issues and optimizing costs.

Lead technical design and architecture of large-scale Ceph clusters, drive capacity planning and major upgrades, resolve complex cross-functional production incidents, establish automation and reliability standards, and mentor engineers on advanced Ceph operations to scale the global storage platform.

Build and maintain Python backend services and APIs for an economics engine: design scalable time-series processing, optimize MongoDB schemas and queries, deploy containerized services on GCP, ensure testability and code quality, use AI tooling to accelerate delivery, and own features end-to-end including monitoring and documentation.

Lead enterprise data architecture and platform engineering efforts using Databricks Lakehouse. Design scalable cloud-native data platforms, implement medallion architectures, enable data governance and AI/ML workloads, build automation and CI/CD for Databricks, and mentor teams while collaborating with stakeholders on strategy and delivery.

Build and maintain full-stack product features, backend services, APIs, data pipelines, and AI integrations to transform customer interaction data into AI-powered experiences. Collaborate with cross-functional teams to design, test, and support production systems, internal tools, and user-facing interfaces. Own ambiguous problems end-to-end and raise engineering quality across the data and AI platform.

Design, build, and operate reliable backend systems while mentoring engineers, participating in design discussions, and improving system performance.

Embedded with strategic customers, own end-to-end design, build, and production rollout of cloud infrastructure for large-scale GPU/HPC AI workloads. Build compute orchestration, platform services, onboarding sandboxes, and reliability/security tooling. Turn field learnings into reusable platform capabilities and partner with Product and Engineering to productize them.

The Lead Systems HPC Engineer will optimize GPU clusters' performance, troubleshoot issues, integrate new hardware, and collaborate with teams on system-level software development.