Top Senior Python Jobs in Miami, FL

Build scalable data pipelines and processing systems for AI model training at petabyte scale. Responsibilities include discovering audio data sources, improving dataset quality and processing efficiency, optimizing throughput and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement.

Build and operate large-scale audio data pipelines for AI model training. The role involves discovering data sources, optimizing data processing for quality, throughput, and cost, partnering with AI scientists, and owning engineering projects from discovery through continuous improvement.

Owns end-to-end post-sales technical support for federal and special-program customers in secure, classified, and air-gapped environments. Diagnoses issues across Linux, compute, GPUs, networking, storage, cloud, and applications; collects and sanitizes diagnostics; manages escalations; maintains hardened deployments; supports hardware replacement; writes knowledge-base content; and provides customer and pre-sales support. The role includes on-call rotations, secure-facility work, and regional and domestic travel.

Build and evolve scalable full-stack systems for People Data Labs’ APIs, self-serve products, and customer success tools. Responsibilities include designing frontend and backend architecture, developing React and Python applications, ensuring data integrity, implementing reliable APIs, optimizing performance, operating production services, collaborating with stakeholders, writing technical designs, mentoring engineers, and improving development practices.

Lead the technical direction and architecture of the Foundations platform team, owning authentication, authorization, SSO, secrets management, tenancy, and core platform services. Design APIs, drive services through launch, make technical decisions, establish engineering standards, and mentor engineers without formal management authority. Partner with engineering and product leaders to align execution with priorities.

Leads and grows the Payments engineering team while remaining hands-on in software development. Designs scalable backend systems using .NET, databases, messaging, Docker, and AWS. Manages engineering and QA professionals, mentors team members, prioritizes initiatives, and collaborates with product and business stakeholders. The role combines approximately 60% engineering with 40% people and project management.

Build and operate the platform supporting Honeydew’s digital dermatology product. Responsibilities include migrating data infrastructure to RDS, strengthening AWS security and compliance, standardizing logging, developing AI-assisted vulnerability remediation workflows, creating infrastructure and automation, supporting feature teams, and reviewing code. The role requires backend service and API development, platform security, infrastructure as code, CI/CD, and strong data and architecture skills.

Design, develop, deploy, and maintain scalable backend services, APIs, and frontend applications. Own projects from architecture through monitoring, collaborate with product and design teams, participate in technical and code reviews, troubleshoot complex issues, and improve engineering practices. The role focuses on secure, reliable systems across cybersecurity, AI, and distributed systems while providing technical guidance to peers.

Leads a distributed engineering team while contributing hands-on to Azure software development, observability services, cloud architecture, and production reliability. Responsibilities include technical direction, coding, design reviews, customer engagements, incident response, on-call operations, reusable engineering assets, cross-team initiatives, and people development. The role translates customer needs into Azure platform improvements and balances delivery, engineering strategy, service resilience, and talent development.

Designs and manages cloud infrastructure across development, staging, and production using Terraform and AWS. Builds containerized environments with Docker, ECS, and Kubernetes; develops CI/CD pipelines; manages networking, routing, APIs, WAF, monitoring, and autoscaling. Troubleshoots infrastructure and deployment issues, optimizes performance and reliability, and collaborates with development and QA teams. The role also supports cloud-agnostic architecture, observability, Linux administration, and automation scripting.

Build and maintain high-performance, resilient SDKs across multiple programming languages and platforms. Develop features, improve reliability, collaborate with engineering and product teams, maintain open-source repositories, and influence technical and product decisions. The role requires strong software engineering fundamentals, polyglot development ability, library-building experience, production-quality coding, and expertise in unit, integration, load testing, and benchmarking.

Leads architecture, hands-on software development, deployment, and production issue resolution for strategic customer projects. Drives AI innovation, platform resiliency, security, observability, performance, and operational improvements. Partners with executives, engineering, product, and customer success teams to prioritize strategic programs, improve customer value, share technical best practices, and remove production blockers.

Develop and maintain enterprise Ansible automation, infrastructure-as-code solutions, REST APIs, scripts, CI/CD pipelines, and integrations across complex infrastructure environments. Manage automation projects through the full software development lifecycle, support production systems, document solutions, troubleshoot issues, and collaborate with infrastructure, security, and service teams. The role requires secure coding, Agile delivery, on-call participation, U.S. citizenship, and eligibility for Public Trust clearance.

Develops high-quality software and AI-powered prototypes for national security missions. Responsibilities include architectural design, feature development, automated testing, backlog grooming, sprint execution, API and SDK development, integration debugging, and research involving LLMs, embeddings, and smaller trained models. The engineer independently leads focused efforts while collaborating with product and engineering teams, using modern DevSecOps and CI/CD practices.

Lead the evolution of Azure infrastructure toward Kubernetes-based, microservices-oriented systems. Design reliable and scalable cloud infrastructure, observability, networking, CI/CD pipelines, and Infrastructure-as-Code. Drive incident response, cost optimization, capacity planning, performance improvements, and automation while partnering with engineering and data teams. Document best practices, mentor colleagues, and support platform strategy in a healthcare environment with PHI, access control, and audit requirements.

Leads distributed software development teams across legacy, modern, and cloud-native applications. Oversees planning, Agile delivery, engineering standards, DevSecOps, CI/CD, AWS and Kubernetes deployments, AI-assisted development, governance, compliance, modernization, and stakeholder communication. Manages team performance, mentoring, workload allocation, hiring, retention, and culture while ensuring secure, scalable, high-quality application delivery.

The Staff Quality Engineer will establish testing strategy, expand scalable end-to-end automation, close coverage gaps, and define quality metrics and release gates. They will test AI-powered features, collaborate with developers on test planning, use AI tools for testing and triage, and coach engineering teams on quality-by-design practices. The role requires influencing multiple teams independently without a dedicated QE team or manager.

Design and build robust backend services and secure APIs for finance and reader applications. Implement authentication, payments, subscriptions, and finance workflows. Design Postgres/Redis schemas, integrate with financial APIs (BSE Star MF, NSE) and DRM services, and ensure compliance-friendly data handling.

Own and evolve production infrastructure for AI workloads, including Kubernetes, cloud-native migrations, scheduling, orchestration, observability, infrastructure as code, deployment workflows, security, reliability, and incident recovery. Partner with engineering and business operations teams to build dependable platform capabilities. The role requires deep production Kubernetes experience, strong cloud and Linux fundamentals, architectural judgment, automation skills, and end-to-end ownership of infrastructure systems.

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.

Designs scalable, secure, resilient cloud and data architectures for high-volume services. Evaluates cloud technologies, develops reusable Terraform infrastructure and automation, and serves as a database architecture expert for PostgreSQL, Oracle, MongoDB, Redis, and Valkey. Builds prototypes and reference implementations, designs highly available distributed database systems, coaches engineers, partners with product and SRE teams, and converts validated concepts into production-ready architecture patterns.

Design, build, and operate backend services supporting external penetration testing, including Python APIs, workflow orchestration, ETL pipelines, AWS data lakes, GraphQL and graph APIs, Kubernetes infrastructure, and observability systems. Own service performance, scalability, uptime, deployment, and production operations while collaborating with product, design, and frontend teams. Contribute to architecture, technical documentation, platform stability, and user-facing launches.

Design, operate, and evolve production GCP infrastructure, including GKE clusters, networking, IAM, shared services, and Terraform automation. Troubleshoot complex Kubernetes, Linux, networking, DNS, and distributed-systems issues; improve observability, security, scalability, reliability, and cost efficiency. Lead upgrades, migrations, architecture improvements, technical reviews, and mentorship while partnering with Platform Engineering, SRE, and Security teams.

Develop and optimize process models and techno-economic analyses for direct air capture demo and production facilities. Translate Aspen models into equipment sizing, cost estimates, process documentation, and vendor-ready specifications. Refine heat and mass balances, evaluate operating scenarios, support equipment selection, and identify energy, capital, and operating cost reductions. Collaborate with engineering, R&D, project management, vendors, and external design firms while presenting technical and financial findings to leadership, investors, and stakeholders.

Provide technical leadership for site reliability engineering, applying software engineering practices to large-scale operations. Design automated, repeatable operational solutions; monitor service objectives, application performance, and business metrics; improve resiliency, efficiency, and cost. Support cloud and on-premise infrastructure, production applications, deployment automation, testing, and vulnerability response. Partner with software development, security, and business teams while promoting Agile practices, change management, training, and operational health.