Top Remote Python Jobs in Houston, TX

Build and maintain large-scale healthcare data platform software using HL7/FHIR, Apache Spark, Python, Scala, Databricks, and cloud technologies. Shape technical roadmaps, architecture, and implementation approaches; collaborate with product and business stakeholders; maintain CI/CD and staging environments; and mentor junior engineers. The role requires deep healthcare data expertise, technical leadership, and experience with modern software engineering and integration practices.

Leads a team responsible for simulation-based verification and validation of autonomous trucks. Defines V&V strategy, scenario coverage, test campaigns, toolchain requirements, and safety-case evidence aligned with automotive standards. Partners with product, systems, safety, engineering, tools teams, and vendors to establish release criteria, identify testing gaps, analyze results, and report risks and progress to leadership. The role also involves team development, simulation scenario management, and advancing autonomous vehicle validation practices.

Build and maintain full-stack software supporting patient-centered healthcare products. Contribute to architecture, technical standards, code reviews, design discussions, and reliable implementation. Collaborate with product managers, designers, and stakeholders, while advocating for privacy, security, and access to care. Mentor engineers, document knowledge, identify technical improvements, and help shape project direction. The role requires backend, database, cloud, and AI development-tool experience in a fully remote environment.

Leads a team of 4–6 senior network engineers while providing hands-on support for complex customer environments. Oversees daily operations, escalations, incident and major incident management, root cause analysis, preventive measures, performance reviews, on-call scheduling, and workload distribution. Troubleshoots and optimizes Cisco, Nexus, Meraki, Palo Alto, Check Point, F5, and SAN technologies, while supporting monitoring, automation, patching, firmware updates, and hardware lifecycle management.

Owns Site Reliability Engineering for a customer-facing SaaS platform across Azure and Azure Government. Responsibilities include monitoring and observability, incident response, root cause analysis, reliability improvements, automation, infrastructure as code, CI/CD, performance optimization, disaster recovery, and operational security. The engineer will define and track SLIs, SLOs, and error budgets, lead post-incident reviews, reduce operational toil, and collaborate with development teams on scalable, reliable platform operations.

Own the architecture, performance, reliability, and technical direction of high-traffic backend services and public APIs supporting search, browse, autocomplete, and recommendations. Lead distributed-systems design, mentor engineers, drive cross-team projects, participate in on-call and incident response, and balance scalability, latency, cost, and API compatibility.

Build full-stack software, backend services, APIs, frontend experiences, and shared integration capabilities supporting AI initiatives across Keeper’s products. Integrate LLMs, agents, and tool-calling workflows into secure production environments while maintaining zero-knowledge principles. Troubleshoot cross-product systems, improve reliability and observability, contribute to architecture and code reviews, automate testing and CI/CD, and collaborate with AI, product, and engineering teams.

Design, develop, test, and maintain scalable platform software and services. Collaborate with architecture and cross-functional teams, implement platform features, participate in code reviews, document technical specifications, troubleshoot issues, and optimize performance and scalability. The role requires Go development, scripting, Kubernetes, cloud-native technologies, containerization, cloud networking, and CI/CD experience.

Lead backend TypeScript development and maintain services used by ~5M users. Contribute to full-stack features, code reviews, architecture discussions, mentor engineers, and collaborate with PM/design to build React-based web and mobile experiences.

Build Tailscale’s internal AI-enablement tools, workflows, guardrails, and documentation. Partner with engineering leadership and teams to define the AI roadmap, evaluate coding agents and models, improve adoption, and measure effects on velocity and quality. The role involves developing internal developer-facing automation, teaching and influencing engineers, identifying high-leverage AI opportunities, and promoting safe use of AI-generated code in a distributed engineering organization.

Lead reliability, scalability, and operational excellence of large-scale database platforms across cloud and on-prem. Build automation-first database infrastructure (Kubernetes operators, IaC, GitOps), drive monitoring/SLOs, incident leadership, performance and cost optimization, and partner with application teams on safe schema/migration practices. Mentor engineers and evaluate AI-assisted workflows to improve productivity and reliability.

Develop and maintain PX4 autopilot firmware for UAVs, integrating sensors and payloads, and managing testing environments. Collaborate on flight operations and system integration.

Designs and maintains automated testing frameworks for AI-powered applications, APIs, backend services, and distributed systems. Defines test strategies, acceptance criteria, evaluation metrics, tolerances, and quality gates for deterministic and non-deterministic software. Builds regression, integration, API, and end-to-end coverage; evaluates LLMs, agents, prompts, and tool-calling workflows; integrates testing into CI/CD; analyzes failures, telemetry, and logs; reduces flaky tests; and partners with AI, engineering, and product teams on continuous quality practices.

Lead design, development, and operation of highly available AKS Resource Provider and control-plane services. Drive cluster lifecycle, upgrades, networking, security, scalability, observability, resiliency, and incident prevention for large-scale distributed cloud systems. Collaborate across Azure engineering teams, lead architectural decisions, improve tooling and automation, troubleshoot production issues, and mentor engineers while supporting reliable Kubernetes workloads across cloud and edge environments.

Lead the architecture, development, testing, and deployment of hyperscale distributed storage systems optimized for AI and machine learning workloads. Drive innovations in scalability, performance, security, durability, and efficiency while collaborating with AI researchers and cloud infrastructure teams. Mentor engineers, guide technical strategy, and help shape Azure Blob Storage into an AI-native platform supporting zettabyte-scale storage.

Develop, implement, and test embedded software, firmware, and edge solutions for industrial automation, networking, and real-time platforms. Responsibilities span architecture, implementation, integration, verification, test automation, cybersecurity, and transitioning research prototypes into products. The role collaborates with GE Vernova teams, suppliers, government agencies, national laboratories, and universities on energy and government-funded R&D programs. Candidates may also contribute to FPGA development, industrial protocols, real-time systems, and technical proposals and reports.

Supports multi-cloud lab infrastructure across AWS, Azure, and Google Cloud using Terraform, Ansible, and GitHub Actions. Assists with infrastructure-as-code modules, CI/CD pipelines, security tool evaluations, agentic automation, client POC engagements, technical documentation, and findings reports under mentorship. The part-time remote internship provides hands-on exposure to cloud infrastructure, DevOps, cybersecurity tooling, and AI-driven evaluation environments.

Designs and implements spacecraft attitude determination and control, guidance, navigation, and control architectures in embedded C++. Performs mission-specific analysis, simulation, requirements definition, sensor-calibration and geolocation pipeline development, anomaly resolution, and software- and hardware-in-the-loop testing. The role supports on-orbit systems and collaborates across spacecraft engineering disciplines. Remote work is available from approved states, with export-control eligibility requirements.

Principal Software Engineer responsible for operating and improving business-critical data pipelines and infrastructure. Duties include developing monitoring, alerting, logging, CI/CD workflows, scalable data integrations, automated testing, deployment automation, and production support. The role troubleshoots workflow failures, data-quality issues, performance bottlenecks, and infrastructure incidents while collaborating with data engineers, platform engineers, and architects. Preferred experience includes Databricks, Spark, AWS, Terraform, Unity Catalog, Delta Lake, observability, identity management, and enterprise data platform governance.

Build and maintain secure, scalable backend systems for Mindbody products. Design microservices, write tested and maintainable code, monitor applications, participate in reviews, and collaborate with Product, Design, QA, and Engineering teams. The description also includes leadership responsibilities such as managing backend development teams, coaching managers and engineers, establishing delivery processes, and driving technical and organizational improvement.

Leads multidisciplinary design, analysis, and optimization for unmanned aircraft, missiles, interceptors, and munitions. Integrates aerodynamics, structures, propulsion, GNC, CAD, CFD, FEA, and trajectory models into automated optimization workflows. Owns MDAO tool architecture, validation, documentation, and development pipelines; conducts trade studies, correlates models with test data, supports proposals, presents design reviews, and mentors engineers. Requires experience taking MDAO from conceptual sizing through flight testing and fielded hardware.

Design, implement, and operate networking infrastructure for Azure Dedicated private and hybrid cloud environments. Responsibilities include hybrid connectivity, ExpressRoute, SDN solutions, third-party platform integration, network performance and security optimization, live-site operations, automation, observability, troubleshooting, and enabling migration and disaster recovery scenarios.

The Lead Technology Engineer will lead IT systems implementation, ensure network security, manage integrations, and enhance operational efficiency through automation.

Build and operate high-throughput data ingestion and ETL pipelines that transform autonomous pentest outputs into structured, queryable data. Responsibilities include schema design, implementation, testing, deployment, monitoring, data normalization, production troubleshooting, and collaboration on data contracts with downstream teams. The role uses Go and/or Python, message queues, relational and graph databases, Kubernetes, Docker, and AWS. It also provides engineering guidance to less experienced team members.

Build and maintain production full-stack features across Python backends, APIs, AI/LLM workflows, and React frontends. Design integrations, data persistence, event-driven services, and secure cloud-native workloads. Translate designs into accessible interfaces, write tests, participate in reviews, support CI/CD and observability, and diagnose issues across the stack. Collaborate with product, UX, and engineering teams to deliver iterative features in an enterprise AI platform.