Top Remote Python Jobs in Houston, TX

Design and build a scalable, responsive UI; lead frontend architecture and optimization; apply UI/UX best practices; integrate with backend APIs; ensure high web performance and deploy user-facing features.

Full Stack Engineer responsible for building responsive frontends (JS/TS, React preferred) and backend services (Python, Go, or Node.js/TypeScript), designing RESTful APIs, managing databases (Postgres/MongoDB), and deploying on cloud (AWS). Collaborate with teams, optimize performance, and apply DevOps practices (Docker, Kubernetes, CI/CD). Requires strong problem-solving, communication, and 3+ years of experience.

Build and evolve Polar’s finance and monetization platform for AI products. Own product development end-to-end across frontend and backend systems, create intuitive developer experiences, ship reliable software quickly, engage with merchants, and translate feedback into product improvements. The role requires strong technical foundations, product judgment, design sensibility, autonomy, engineering quality, and comfort working across the stack. Payments, billing, developer tools, open-source contributions, and side projects are valued.

Build and operate reliable platform systems supporting billing, payments, financial workflows, and usage-based software. Responsibilities include evolving cloud infrastructure, improving observability and incident response, creating developer tooling and automation, optimizing distributed backend systems and databases, and ensuring security, auditability, and financial data correctness. The role requires pragmatic technical judgment, product awareness, end-to-end ownership, and experience operating production systems at scale.

Own the full technology stack for an AI food assistant, taking an iPhone app from internal testing through beta and scale. Responsibilities include backend and mobile development, architecture, infrastructure, deployments, monitoring, AI feature reliability, catalog and personalization systems, creator and internal tooling, App Store releases, security, and engineering standards. The role also involves product decisions, household research, technical leadership, and end-to-end ownership in a founding-team environment.

Lead as a customer‑embedded principal engineer to design, build, and ship production-grade solutions. Translate business needs into technical approaches, influence senior stakeholders, accelerate delivery in ambiguous environments, and transition work to FDE crews while driving long-term account impact.

Build and maintain scalable backend services, RESTful and GraphQL APIs, database schemas, and cloud infrastructure. Own architecture decisions, optimize performance and reliability, improve CI/CD practices, collaborate across product and engineering teams, lead architecture sessions, review code, and mentor junior developers.

Own the durability, recoverability, performance, and security of a production PostgreSQL/RDS fleet supporting a live trading platform. Lead replication, failover, backup and restore, disaster-recovery drills, data lifecycle management, access control, encryption, and database observability. Investigate engine-level performance issues including WAL contention, replica lag, bloat, and locking. Build infrastructure and AI-assisted operational tooling while documenting runbooks and reliability decisions.

Build and operate secure, scalable multi-cloud infrastructure across AWS, GCP, and networking platforms. Develop self-service tooling, infrastructure-as-code defaults, cloud guardrails, and standardized platform patterns. Lead cross-team infrastructure initiatives, technical investigations, and operational improvements while partnering with security, compute, routing, and other infrastructure teams.

Design, scale, and operate Runpod’s distributed storage platform across network volumes, local NVMe, and S3-compatible object storage. Tune storage and high-speed network performance, lead capacity expansions and migrations, write production automation and control-plane code, extend APIs, and build observability, dashboards, SLOs, and alerts. The role also participates in on-call operations, incident response, infrastructure-as-code practices, and long-term architecture decisions for petabyte-scale AI infrastructure.

Investigate voice AI campaign and platform issues by analyzing calls, transcripts, logs, configurations, and integration data. Reproduce and document bugs, triage root causes, perform pre-launch and ongoing conversation QA, and develop test plans, regression suites, quality metrics, and automation. Collaborate with engineering, deployment, clinical, and nursing teams to improve agent behavior, workflows, handoffs, scheduling, and outcome capture.

Lead enterprise B2B integration projects for strategic customers using APIs, webhooks, connectors, cloud services, and scalable integration architectures. Translate business requirements into technical designs, build and review code, manage complex projects, troubleshoot deployments, and advise customers and internal teams on integration best practices. Collaborate with product, sales, support, and developer ecosystem teams while supporting multiple customer engagements and improving professional services methodologies.

Provides technical leadership for Azure SQL databases supporting a highly available Azure service. Responsibilities include database performance tuning, reliability and capacity planning, schema changes, data migrations, observability, incident response, root cause analysis, operational automation, and technical strategy. The role partners with software engineers, SREs, and architects to improve scalability, durability, cost efficiency, and long-term service reliability across teams.

Build and own the technical roadmap: design AI-first interfaces and APIs, architect scalable ETL pipelines, develop data models for ML features, ship autonomous B2B workflows (PO generation, vendor sync, schedule optimizations), and establish engineering standards, CI/CD, and mentoring.

Designs and develops FPGA SmartNIC networking acceleration for Microsoft Azure. Responsibilities include hardware architecture evaluation, RTL coding in Verilog/SystemVerilog, simulation, hardware testing, debugging, verification, scripting, software development, Agile collaboration, and production DevOps support. The role partners across hardware and software teams to deliver cloud networking infrastructure, including SDN capabilities, packet manipulation, and performance improvements.

Design and implement PostgreSQL internals and indexing/query features for large-scale document workloads, extend query engine with BSON-aware operators and custom scan nodes, tune index pruning and storage, profile distributed systems for performance, collaborate with open-source DocumentDB/PostgreSQL communities, and participate in design/code reviews.

Lead test strategy for Akamai’s custom Linux kernel and OS imaging process. Design scalable automated test frameworks, validate hardware compatibility, performance, reliability, and security, and develop test suites for new hardware platforms. Troubleshoot low-level system issues, enhance build and continuous testing infrastructure, establish quality standards, and mentor junior engineers.

Interns gain hands-on experience with Azure cloud engineering, Terraform infrastructure as code, CI/CD, SQL and data engineering, C#/.NET API development, enterprise IT operations, troubleshooting, security, and technical documentation. The role includes completing a defined modernization or technical project from requirements through deployment and presentation while learning enterprise architecture, monitoring, identity, secrets management, and production-support practices.

Build and maintain AI-native skills taxonomies, capability models, learning context, instrumentation, and APIs for Databricks employees, customers, and partners. Develop LLM-driven extraction, agentic pipelines, drift and gap detection, and live capability measurement. Partner across content, curriculum, certification, product, and enablement teams to ensure technical skills are consistently defined, assessed, and applied. Use Python, SQL, analysis, and clear writing to advance strategy as an individual contributor.

Own enterprise customer technical cases from triage through resolution, troubleshooting Kubernetes, ECS, Docker, cloud infrastructure, deployments, connectivity, and CI/CD issues. Perform root-cause analysis, lead customer calls, build diagnostic scripts and tooling, contribute small product fixes, and document reusable runbooks. The role also includes occasional customer build engagements and collaboration with Product and Engineering.

Design, build, and maintain scalable cloud infrastructure using AWS, GCP, or Azure. Implement SRE practices, monitoring, observability, capacity planning, Kubernetes and Helm deployments, CI/CD pipelines, automation, and cloud security controls. Collaborate with cross-functional teams, ensure compliance, and mentor engineers while improving reliability, availability, scalability, and performance.

Deploy, upgrade, and maintain High-Speed Data infrastructure (DNS, DHCP, DOCSIS). Administer CentOS/RHEL systems, automate with Python/Ansible/Shell, troubleshoot escalations, create LLDs, run upgrades, train teams, perform on-call duties, and ensure security and high availability.

Build Doowii’s conversational analytics platform across frontend, backend, data interaction, and infrastructure. Responsibilities include creating data-query interfaces, developing APIs, integrating AI-driven features, optimizing query and storage performance, managing AWS and GCP systems, designing data models, and maintaining ingestion pipelines involving NiFi, Kafka, Iceberg, and BigQuery. The role also involves model evaluation, schema evolution, change data capture, high-throughput streaming, automation, and rapid startup iteration.

Lead technical strategy and execution for multi-quarter initiatives, build and maintain software systems using AI, mentor and elevate engineers, collaborate across disciplines, and protect user privacy and security. The role involves working in an AWS and Kubernetes environment with technologies including Python, TypeScript, React, Go, Airflow, dbt, and Claude Code.

Own operations and reliability for hyperscale Azure GPU clusters and interconnect fabrics. Lead production incident triage, mitigation, recovery, root-cause analysis, and cross-stack debugging across hardware, PCIe, GPUs, firmware, drivers, and software. Develop automation, telemetry, diagnostic tools, operational playbooks, and escalation procedures to improve observability and reduce mitigation time. Partner with engineering teams and manufacturers to resolve systemic issues affecting AI training stability, GPU availability, and customer SLAs.