Top Remote Python Jobs in Miami, FL

Lead and coordinate high-severity production incidents for cloud-native services, drive root cause analysis and reliability improvements, own incident communications to stakeholders and customers, and mentor peers while maintaining incident playbooks and observability-driven diagnostics.

Leads the architecture, design, implementation, testing, and delivery of backend software for Slate’s digital customer experience. Owns code quality, system reliability, functional and integration testing, and technical decision-making. Collaborates with UX and product teams, leads code and design reviews, simplifies complex solutions, and mentors engineers while supporting career development.

Design, develop, and maintain scalable AI-forward APIs, MCPs, and services for Microsoft 365. Lead features from concept through launch, write reusable code, document designs, estimate work, and support production services through on-call responsibilities. Improve reliability, performance, and scalability while mentoring engineers and establishing technical best practices across teams.

Design and build distributed storage systems optimized for AI and machine learning workloads at hyperscale. Lead architecture, development, testing, deployment, scalability, performance, security, and efficiency initiatives for zettabyte-scale Azure storage. Collaborate with AI researchers and cloud infrastructure teams, mentor engineers, evaluate emerging technologies, and solve complex problems involving availability, durability, replication, high-performance I/O, metadata, indexing, caching, and data placement.

Design and implement scalable, durable cloud storage services for Azure Archive Storage. Collaborate with hardware/firmware teams, lead design and feature implementation, mentor engineers, act as DRI and on-call owner, and improve availability, reliability, performance, and observability of large-scale distributed storage systems.

Lead technical ownership of InfiniBand and GPU interconnect fabric operations for hyperscale AI supercomputers. Drive incident response, deep multi-layer debugging across hardware/firmware/drivers/OS, and define failure models, playbooks, telemetry, and automation to improve reliability, observability, and scalability of GPU clusters and platform SLAs.

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, GPUs, PCIe, firmware, drivers, and software. Develop automation, telemetry, diagnostics, playbooks, and escalation frameworks to improve observability, operational readiness, and mean time to mitigation for large-scale AI and HPC workloads.

Evaluate AI coding-agent interactions for usefulness, correctness, engineering judgment, reasoning quality, and overall developer experience. Provide rigorous, opinionated feedback, distinguish response-quality levels, and help define standards for excellent interactions with tools such as OpenAI Codex, Claude Code, and Cursor. The role requires deep software engineering experience, familiarity with AI-assisted development workflows, and the ability to assess code and explanations without reviewing every line.

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.

Design, build, and maintain backend services in TypeScript for millions of users; develop full‑stack features with React/React Native; participate in code reviews; provide technical leadership, mentorship, and architecture guidance; collaborate with PM and design; use monitoring/metrics and Agile practices to deliver scalable, user-focused products.

Lead test architect for end-to-end integration testing of a complex genomics product portfolio. Design contract-first validations (OpenAPI/Avro), build resilient API and event-driven test frameworks, embed LLM-driven test generation and log analysis into CI/CD, mentor SQEs, enforce staging guardrails, and run chaos/resiliency experiments across distributed microservices.

Own and evolve Quansight's multi-cloud infrastructure, lead client infrastructure engagements end-to-end, build observability and CI/CD systems, mentor teammates, and dedicate substantial time to contributing and maintaining open-source infrastructure projects.

Designs, deploys, integrates, monitors, maintains, and troubleshoots storage and IT infrastructure, including SAN, NAS, object storage, VMware, networking, backups, and disaster recovery systems. Implements automation, security controls, patches, and system upgrades while maintaining documentation and compliance. Collaborates with cross-functional teams, participates in incident response and recovery planning, supports system rollouts, and mentors junior engineers. Requires occasional after-hours work and on-call availability for critical incidents.

Design, build, and manage scalable GCP cloud infrastructure, including compute, storage, networking, Kubernetes, monitoring, and IAM. Automate provisioning with Terraform, improve platform reliability, security, performance, and cost efficiency, and support disaster recovery. The role also documents infrastructure practices, collaborates across technical teams, and mentors junior engineers.

Designs, maintains, and modernizes production system integrations and customer-hosted Linux infrastructure. Responsibilities include data interfaces, monitoring, troubleshooting, releases, backups, disaster recovery, security, migrations, CI/CD adoption, documentation, customer coordination, and on-call support. The role works with legacy systems in healthcare environments under HIPAA requirements and uses Claude Code for scripting and code review. It requires strong Linux administration, Bash scripting, Git, build and release management, secure data transfer, and production systems experience.

Develop and operate high-throughput, low-latency telemetry pipelines and cloud services for Azure AI/HPC infrastructure. Build observability, monitoring, analytics, and automation capabilities; own architecture through deployment and operations; and lead incident response, root-cause analysis, reliability improvements, and operational readiness. Partner across engineering and platform teams, influence technical roadmaps, mentor engineers, and apply distributed systems, AI infrastructure, and cloud operations practices at hyperscale.

Lead technical strategy and architecture for Azure Storage geo-replication, data protection, failover orchestration, and business continuity. Drive cross-team delivery, operational excellence, telemetry, automation, AI-assisted operations, and represent the team in executive and customer engagements.

Lead and grow a distributed software engineering team building Azure Kubernetes Service infrastructure. Define architecture, drive design reviews, ensure security, reliability, observability, CI/CD, and operations at scale. Guide implementation, incident response, and continuous improvement while coaching engineers and aligning stakeholders across Azure product teams.

Leads the design, implementation, optimization, and support of highly scalable Azure Storage services. Responsibilities include end-to-end performance testing, benchmarking, automation, profiling, bottleneck and root-cause analysis across compute, storage, and networking layers, KPI definition, scaling recommendations, and operational incident response. The role collaborates across teams, drives project and release plans, supports reliable and secure services, and mentors engineers while participating in on-call responsibilities.

Design and deliver large-scale, resilient AI and Kubernetes infrastructure for hybrid environments. Implement, optimize, and maintain cloud-native, container orchestration solutions; integrate AI capabilities; participate in on-call rotations; mentor engineers and drive reliability, observability, and performance at scale.

Design, implement, debug, and ship features for Azure Storage front end at cloud scale. Drive design, dependency identification, automation, reliability, observability, and on-call incident response while collaborating with stakeholders and mentoring engineers.

Design and deliver large-scale, cloud-native and AI-enabled Kubernetes/AKS solutions. Implement, optimize, and maintain Kubernetes components and container orchestration across Azure, on-prem, and edge. Integrate AI capabilities, participate in on-call rotations, mentor engineers, and collaborate cross-functionally to improve reliability, observability, performance, and operational consistency at scale.

Lead investigation and mitigation of complex distributed storage issues for Azure Managed Disks. Design algorithms for load distribution, monitor system behavior, debug performance and availability problems, collaborate across teams, mentor engineers, act as on-call DRI, and improve observability and reliability at hyperscale.

Own and administer the Redwood RunMyJobs platform, including scheduling, workflow orchestration, job dependencies, monitoring, troubleshooting, integrations, configuration, patching, and security. Develop automated batch workflows and support file transfers, APIs, CI/CD, cloud environments, and mainframe systems. Partner with architects, engineers, developers, and IT stakeholders to translate requirements into reliable automation solutions and improve operational processes.

Lead customer-facing, production-grade data and AI solutions on Databricks: design architectures, implement data pipelines and ML integrations, embed with stakeholders, deliver projects, and produce reusable accelerators and best practices.