Top Remote Python Jobs in Washington, DC

Own production operations and highly available cloud infrastructure for regulated government environments. Lead incident response, root-cause analysis, disaster recovery testing, compliance operationalization, audit readiness, vulnerability management, and continuous monitoring. Build automation, secure CI/CD pipelines, infrastructure-as-code, observability, and compliance tooling across Kubernetes, Linux, containers, and cloud platforms. Partner with security, compliance, and engineering teams to improve reliability, deployment safety, and regulatory sustainment.

As a Senior Engineer, you will develop and maintain backend applications using Go, Python, and Java, influence team culture, mentor colleagues, enforce processes, and work on innovative technology solutions in civic healthcare.

Design, develop, and maintain scalable web and backend applications, public REST APIs, automated testing frameworks, and cloud-native services. Improve scalability, stability, monitoring, auto-scaling, CI/CD, security, and reliability. Conduct code reviews, troubleshoot production issues, document root causes and operational procedures, and collaborate with distributed engineering teams to deliver fleet-management platforms.

Embed with enterprise customers to design, build, and deploy production-grade integrations and data pipelines. Own technical discovery, end-to-end integration lifecycle, AI agent orchestration, customer technical relationships, and feedback to product and engineering. Produce runbooks, templates, and durable handoffs.

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.

Design and deliver distributed storage systems for AI and machine learning workloads at hyperscale. Lead architecture, development, testing, deployment, and innovations in scalability, performance, security, and efficiency. Collaborate with AI researchers and cloud infrastructure engineers, mentor engineers, and guide technical strategy for high-availability, durable, high-performance storage supporting training and inference.

Design, build, and operate core platform infrastructure on AWS using Terraform and Kubernetes. Own end-to-end projects, CI/CD pipelines, observability, security best practices, and production reliability while contributing to architecture decisions, documentation, runbooks, and mentoring. Participate in on-call rotation and automate recurring work.

Lead a software engineering pod while contributing hands-on code to build and scale SaaS platform features. Responsibilities include architecture and technical design, production development, code reviews, troubleshooting, planning, mentoring, cross-team collaboration, AI-assisted development, and ensuring maintainable, secure, scalable, high-quality delivery.

Designs and delivers secure, scalable AWS and Azure cloud solutions for application and data workloads. Translates customer requirements into architectures, develops Terraform infrastructure-as-code modules, and integrates CI/CD, automation, networking, identity, security, monitoring, and recovery capabilities. Owns solutions from discovery through implementation and operational transition while collaborating with Agile Cloud DevOps, security, infrastructure, and application teams. Supports specialized scientific and research platforms and provides trusted technical consulting to customers.

Deploys, hardens, troubleshoots, and modernizes Windows and .NET applications across on-premises environments and AWS. Responsibilities include Terraform infrastructure, CI/CD pipelines, SQL Server and Amazon RDS administration, load balancing, WAF configuration, observability, certificate management, automation, migrations, incident response, documentation, and collaboration with application owners. The role is remote but requires weekly onsite availability in Rockville, Maryland, and may involve occasional after-hours maintenance or outage troubleshooting.

Designs and delivers secure, scalable cloud solutions across AWS and Azure for application, data, scientific, and research workloads. Partners with customers to translate requirements into architectures, develops Terraform infrastructure and automation, integrates DevOps and CI/CD capabilities, and manages solutions through implementation and transition to operations. Responsibilities include cloud networking, identity, security, monitoring, backup and recovery, troubleshooting, documentation, technical reviews, and collaboration within an Agile Cloud DevOps team.

Design, build, and optimize scalable cloud and web software with focus on infrastructure, performance, and hardware integration for IoT devices. Collaborate with hardware teams to ensure connectivity and high availability, implement new features, and improve system efficiency.

Develop open source SDKs, enterprise APIs, UIs, and backend systems supporting large-scale computer vision datasets. Build scalable, maintainable, performant, and well-tested software for unstructured data and AI workflows. Contribute to enterprise deployments across customer clouds and on-premises environments, while improving tooling, automation, engineering practices, and open source community initiatives in a remote-first team.

Develop and maintain microservices-based, real-time software for mission-critical air traffic systems. Collaborate with product, systems engineering, QA, DevOps, and platform teams in an Agile/SAFe environment. Translate requirements into reliable solutions, integrate APIs, databases, messaging systems, and external services, and contribute to design and technical decisions. Apply CI/CD, DevSecOps, automated testing, troubleshooting, performance tuning, and AI-assisted development tools. The role is fully remote and requires Public Trust eligibility and U.S. citizenship.

Design, build and maintain Microsoft Cloud applications using Power Apps/Pages and Azure services. Implement Entra ID authentication, Azure Functions/App Services, Logic Apps and Blob storage. Create Azure Data Factory pipelines and APIs (REST/GraphQL), integrate external services and LLM data pipelines, and ensure performance, security, and scalability while collaborating with customers to turn requirements into streamlined apps.

Lead the architectural vision for cloud-based platform solutions, including scalable AWS infrastructure, integration flows, APIs, IAM governance, networking, observability, and CI/CD pipelines. Design secure, highly available platforms connecting RPA processes, enterprise applications, internal services, and downstream systems. Provide technical leadership, stakeholder management, architecture documentation, mentoring, and engineering best practices while supporting enterprise DevOps, platform engineering, and integration initiatives.

Provides mainframe patch-management expertise using SMP/E and z/OSMF. Responsibilities include CVE reporting, patch automation, response modeling, validation cadence, package stability reviews, dashboard improvements, baseline dataset development, vulnerability-tool integration, and secure patch deployment. The role also develops AI-driven prompts and automation for testing, RFB validation, and impact analysis while supporting z/OS and ISV software installation, maintenance, customization, and testing.

Validate and implement AI fencing controls across z/OS environments through adversarial testing, monitoring, alerting, forensic analysis, and sanitized validation. Design disruptive AI testing labs, test non-privileged user operations, support secure AI adoption, and assess GenieZ production readiness. Requires deep z/OS internals expertise, catalog management, USS security, software installation, complex troubleshooting, advanced testing, REXX, Python, and 10+ years of experience.

Build and maintain scalable backend systems and data pipelines for healthcare workflows. Collaborate cross-functionally to automate provider and patient workflows, prototype features, ship production-ready code, and ensure systems are maintainable and scalable.

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.

Designs and governs scalable, secure, cost-effective Google Cloud solutions across enterprise IT environments. Leads cloud adoption, develops standards and roadmaps, integrates GCP with on-premise and third-party platforms, applies AI and automation, supports high-priority troubleshooting, manages vendors, and communicates architecture decisions to technical and executive stakeholders. Provides training and ensures compliance with enterprise security and technology standards.

Develop distributed, production-grade microservice systems and scalable data-processing infrastructure on Linux. Lead service mesh, contract-first API, gRPC, and Protocol Buffers initiatives; design fault-tolerant architectures and observability systems; operate containerized distributed platforms; and mentor junior and mid-level engineers. The role also emphasizes AI-assisted development, technical communication, and documentation, with preferred experience in industrial automation, monorepos, real-time processing, edge computing, and infrastructure as code.

Build and maintain Django-based web applications, design RESTful APIs, implement frontend features (HTML/CSS/JS), optimize performance and security, collaborate with cross-functional teams throughout the development lifecycle.

Leads functional and automated testing for complex modern, cloud-based applications. Develops test strategies, plans, cases, and automation for unit, API, integration, UI, performance, security, and regression testing. Validates Kafka-based workflows, microservices, serverless systems, data pipelines, and CI/CD releases. Partners with engineering and DevSecOps teams on defect prevention, security, observability, environment readiness, root-cause analysis, and operational quality. Maintains audit-ready documentation and communicates risks and recommendations to stakeholders.

Build full‑stack web features from zero to one, integrate with third‑party APIs, design and manage state machines for financial workflows, own features through launch and post‑launch customer iteration, and maintain high code quality and accountability.