Top Senior Python Jobs in Miami, FL

Build and enhance scalable full-stack applications and microservices using React and Java or Python. Diagnose performance and architectural issues, develop production-grade user interfaces, collaborate in Agile environments, and deliver cloud-based solutions. The role includes end-to-end implementation ownership, technical decision-making, team leadership, mentoring, and applying AI-assisted development tools. Work is remote eligible and supports mission-critical customer systems.

Build and improve scalable, secure, performant web applications and data pipelines for healthcare challenges. Develop technical roadmaps with engineering, product, and business stakeholders using Agile processes. Mentor junior engineers, conduct thorough code reviews, and promote observability, testing, alerting, metrics, and frequent incremental releases. Work with large-scale data processing, databases, APIs, cloud technologies, containerization, orchestration, and CI/CD systems.

Develop and maintain automated front-end, backend, and API testing frameworks using Python and tools such as Cypress and Playwright. Define manual and automated testing strategies, perform functional, performance, non-functional, and security testing, and integrate quality assurance into CI/CD pipelines. Collaborate with development teams, technical leaders, and clients to deliver scalable, reliable enterprise software.

Develop and configure enterprise-scale digital software solutions for asset performance management and predictive analytics. Responsibilities include translating customer requirements into software architectures, designing and implementing applications, documenting solutions, testing technologies, supporting customer implementations, and collaborating with subject matter experts, project managers, product managers, and development teams. The role also involves presentations, scalable application development, secure distributed architectures, and occasional customer project travel.

Build and lead a greenfield cloud platform supporting application, data, and AI workloads. Responsibilities include managing Terraform infrastructure, production EKS clusters, Helm deployments, CI/CD pipelines, security controls, observability, cloud cost allocation, and developer golden paths. The role establishes engineering standards, supports regulated-data compliance, partners across engineering teams, reviews infrastructure changes, mentors engineers, and writes production code while ensuring reliable, secure, and cost-effective service delivery.

Design, implement, and maintain low-latency exchange network infrastructure. Configure network devices using Ansible and Python, monitor alerts, resolve incidents, perform root-cause analysis, support customer connectivity and turn-ups, validate products, engineer secure solutions, and coordinate with data center and circuit providers.

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.

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.

Designs, deploys, and operates high-performance InfiniBand and RoCE networking fabrics for GPU clusters, customer connectivity, and multi-site WANs. Manages routing, switching, BGP peering, public IPs, DDoS protection, automation, monitoring, troubleshooting, documentation, capacity planning, and security audits. Partners with the NOC and supports customer network architectures across layers 1 through 7.

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 the hardware lifecycle for GPU and infrastructure assets, including fleet health monitoring, vendor RMA workflows, firmware and BIOS upgrades, burn-in testing, failure investigation, inventory accuracy, capacity planning, spare-parts strategy, runbook creation, and new platform qualification. The role serves as the technical owner of physical compute platforms and supports high-density GPU infrastructure across sites.

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.

Architect, deploy, optimize, and operate large-scale GPU clusters for AI training and inference. Responsibilities include distributed PyTorch and NCCL tuning, GPU networking and storage optimization, scheduling, benchmarking, troubleshooting, automation, monitoring, and performance engineering across compute, networking, storage, and software layers. The role supports production environments with hundreds to thousands of GPUs and partners with ML engineers to improve training scalability and inference efficiency.

Leads the design and implementation of enterprise network automation across on-premises and multi-cloud environments. Develops Infrastructure as Code using Python, Ansible, Terraform, Git, and CI/CD pipelines; automates provisioning, configuration, monitoring, compliance, and lifecycle management. Supports routers, switches, firewalls, and load balancers, troubleshoots incidents, performs root cause analysis, and drives network upgrades and cloud adoption. Establishes testing and engineering standards, mentors junior engineers, creates documentation, and participates in on-call support and frequent travel.

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.

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.

Design, build, test, and operate production-grade, secure, and scalable software and services. Partner with customers to translate requirements into technical designs, drive engineering best practices (CI/CD, testing, observability), deliver end-to-end solutions, lead technical workstreams, and apply AI/LLM approaches where appropriate to produce production-ready outcomes.

Lead backend development to scale and harden API infrastructures, implement unit testing playbooks, optimize core algorithms, support migration from Supabase to a robust cloud provider, ensure system reliability and scalability, collaborate with frontend and DevOps, and integrate AI workflows and RPA where applicable.

The Lead Architect will develop backend services, oversee integration with imaging facilities, set coding standards, mentor engineers, and ensure fault-tolerant systems while adhering to healthcare data standards.

The Sr Staff AV Behavior Safety Engineer leads safety validation for GM's autonomous driving systems, influences launch decisions, and collaborates across teams for safety standards and performance metrics in AV behavior development.

Lead platform engineering for high-scale, multi-region AWS payment infrastructure. Architect immutable, highly available, self-healing systems; automate infrastructure through Terraform, GitOps, CI/CD, and Kubernetes; establish observability with Prometheus, Grafana, and OpenTelemetry; own incident management and resiliency improvements; design private connectivity; and mentor engineers while driving organization-wide platform standards.

Leads the vision, roadmap, and development of an AI-enabled Service Catalog platform. Combines product leadership with hands-on full-stack engineering across web applications, APIs, integrations, workflows, and AI features. Manages engineering and product strategy, defines success metrics, partners with architects and stakeholders, prototypes capabilities, and ensures scalable, secure, responsible solutions with human oversight.

Lead and grow the Product Engineering team to deliver customer-facing web dashboards, APIs, integrations, and AI workflows. Own roadmap execution, collaborate with Product and Design, drive engineering best practices (testing, deployment, observability), provide technical mentorship, and remain hands-on in architecture and code reviews to ensure high-quality, scalable SaaS product delivery.

Perform CFD and 1D lumped-parameter fluid analyses for rocket engines, predict component and system performance, build transient and steady models, support testing and anomaly investigations, recommend design improvements, and mentor peers to grow propulsion fluid-analysis capabilities.

Own and advance Yahoo’s enterprise Node.js development environment, including runtimes, packages, container images, internal integrations, and CI/CD workflows. Manage runtime lifecycles, security updates, dependencies, releases, testing, automation, and troubleshooting. Support GitHub Enterprise and GitLab Enterprise while integrating AI programming tools to improve developer productivity. Partner across engineering and security teams, and document platform changes, migrations, and deprecations.