Top Remote Python Jobs in Washington, DC

Lead the design, development, and implementation of resilient pricing tools using Python and cloud technologies. Improve automation, deployment reliability, testing, documentation, and technical standards. Coordinate complex projects, research new development practices, identify technical blockers, and mentor junior developers. Collaborate with stakeholders while developing expertise in insurance pricing and supporting applications built with technologies such as Streamlit, Flask, Docker, Kubernetes, and cloud compute.

Designs, deploys, and operates high-performance InfiniBand and RoCE networking fabrics for GPU clusters, customer connectivity, and multi-site WAN infrastructure. Manages routing, switching, BGP peering, VLAN/VRF/VPC architectures, automation, monitoring, troubleshooting, documentation, capacity planning, and security audits. Requires deep data center or service provider networking expertise, advanced routing knowledge, and hands-on experience with Arista, NVIDIA, or Cisco platforms.

Administer enterprise database environments supporting high availability, replication, disaster recovery, security, performance, retention, and hybrid-cloud operations. Lead SQL Server infrastructure while supporting Oracle, MySQL, PostgreSQL, and NoSQL platforms. Design zero-downtime upgrades, migrations, failover testing, and modernization roadmaps. Develop automation using Terraform, Ansible, scripting, and CI/CD pipelines; establish operational standards; lead outage response; and mentor distributed operations teams.

The Integration Engineer will lead client onboarding for fraud and compliance products, manage integrations, analyze requirements, and support clients throughout the process.

Lead client onboarding and end-to-end integrations for fraud and compliance products. Translate technical and business requirements into scalable solutions, manage implementation timelines and risks, support customers, maintain API and SDK documentation, analyze SQL and JSON data, build internal automation tools, and provide product feedback to internal teams.

Build and operate enterprise Amazon Connect contact centers and AI agents. Implement generative AI (Bedrock/Claude), serverless backends, CDK IaC, observability, testing, and integrations with CRMs and analytics. Own delivery from code to production, mentor engineers, and support customer-facing technical workstreams.

Own and evolve a secure, cloud-native internal developer platform for a federal health mission. Responsibilities include Terraform and GitOps foundations, multi-tenant Kubernetes on AWS GovCloud, self-service onboarding, MLOps/AIOps, data lakehouse enablement, observability, security automation, compliance artifacts, documentation, and stakeholder partnership. The role requires senior ownership of production platforms and offers opportunities for technical leadership.

Own and scale Cribl’s corporate IT systems, including Okta identity, AWS infrastructure, endpoint management, ServiceNow, SaaS integrations, automation, and AI tool governance. Lead lifecycle workflows, security baselines, compliance reporting, incident escalation, and on-call operations while partnering with Security, Enterprise Applications, Finance, Compliance, and People teams.

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.

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 and support customer integrations by designing workflows across the core product and external platforms such as QuickBooks, Salesforce, and NetSuite. Translate customer requirements into complete solutions, deliver projects on schedule, maintain project documentation, resolve technical challenges, communicate roadblocks, and mentor team members. The role requires API experience across multiple products, scripting expertise, strong communication, adaptability, and attention to detail.

Designs and maintains automated test frameworks for Keeper Secrets Manager APIs, SDKs, integrations, and cloud services. Builds API, integration, and end-to-end tests; integrates automation with CI/CD pipelines; manages Docker and Kubernetes test environments; validates authentication workflows; analyzes failures; and partners with engineering and DevOps teams to improve system testability, reliability, and security.

Deploys and operates secure, scalable AWS cloud platforms across federal environments, including FedRAMP and classified workloads. Builds Kubernetes infrastructure, Terraform modules, Crossplane compositions, CI/CD workflows, automation, telemetry, documentation, and developer tooling. Evaluates technologies, improves deployment processes, manages concurrent initiatives, and supports platform reliability. Requires Go, AWS, Kubernetes, infrastructure-as-code, and federal security knowledge, along with U.S. citizenship and the ability to obtain and maintain a Top Secret clearance.

Combines wastewater process engineering with AI, machine learning, process modeling, digital twins, and optimization. Responsibilities include analyzing treatment data, developing biological and chemical process models, evaluating and troubleshooting facilities, conducting experiments, testing technologies, and implementing predictive or optimization solutions. The engineer collaborates with multidisciplinary project teams and utility clients to improve treatment performance, reliability, energy use, and operational decision-making. Python programming and wastewater modeling platforms are preferred, along with wastewater treatment, nutrient removal, data science, and technical communication expertise.

Designs and builds scalable applications using React and Python, contributing to component development, data storage, deployment practices, performance optimization, testing, and client requirements analysis. The role collaborates with technical leaders, clients, and distributed teams in agile environments, using Git, code reviews, cloud platforms, databases, and AI-native development practices. U.S.-based travel to client sites is required.

Designs, implements, supports, and improves enterprise Azure, hybrid, on-premises, and network security environments. Owns complex routing, switching, firewall, SD-WAN, cloud connectivity, and automation solutions. Provides L3 escalation support, incident triage, root cause analysis, client advisory, documentation, and technical leadership across managed services environments. Mentors engineers, improves standards and monitoring, supports migrations, and automates deployments using infrastructure-as-code and scripting tools.

Implement, support, and troubleshoot ServiceNow Discovery across enterprise environments. Manage MID Servers, Discovery Patterns, Sensors, IRE, CMDB Health, credentials, performance, and cloud resource discovery across AWS, Azure, and GCP. Develop Python automation and use AI-assisted development tools. Support ServiceNow solutions hosted primarily on AWS, participate in live technical interviews, maintain a ServiceNow PDI, and complete background, employment, and certification verification.

Design, develop, and maintain scalable web services for a B2B SaaS application. Write tested code primarily in Go, manage PostgreSQL schemas and queries, and research AI-powered tools for software development and CI/CD optimization. Collaborate with product, design, and engineering teams to deliver user-focused solutions. Mentor engineers, promote best practices, and contribute to technical excellence.

Design, develop, and maintain automated tests for functional, regression, integration, and performance testing. Build test automation frameworks, integrate tests into CI/CD pipelines, analyze results, document defects, and collaborate with development and cross-functional teams to improve product quality and testing processes.

Provides advanced technical support for robotic systems during commissioning and 24/7 customer operations. Diagnoses hardware, software, controls, Linux, network, and automation failures; analyzes logs and telemetry; develops integrations and support workflows; leads major incidents; coordinates engineering, field service, and customer teams; manages cases and corrective actions; validates AI-assisted diagnostics; and mentors engineers while improving system reliability and recovery times.

Designs and builds secure, scalable distributed backend systems using Python and AWS. Responsibilities include event-driven architectures, asynchronous processing, cloud data pipelines, serverless applications, REST APIs, performance optimization, authentication, and cloud security. The role requires strong distributed systems, testing, debugging, and backend development expertise, with GenAI, LLM, RAG, and vector database experience preferred.

Design and optimize networking infrastructure for Azure AI supercomputing clusters. Develop RDMA communication libraries, transport protocols, distributed systems, observability tools, and performance optimizations. Analyze latency, throughput, congestion, scalability, and fault tolerance across large GPU and accelerator environments. Lead technical architecture, write design specifications, resolve complex production networking challenges, and collaborate with hardware, silicon, AI framework, and infrastructure teams.

Design, execute, and analyze functional, regression, integration, system, and performance tests for a web-based observability platform. Create test plans and cases, track defects, collaborate with developers and product, improve QA processes, and potentially build/maintain automated tests. Participate in Agile ceremonies and investigate root causes to ensure timely resolution.

Designs and implements Go-based control-plane software for custom AI inference hardware. Responsibilities span system management APIs, Linux services, hardware interfaces, diagnostics, observability, security, firmware updates, distributed systems, and workload management. The role requires hands-on debugging across application, operating system, firmware, and hardware boundaries, plus technical leadership, mentoring, architecture, and production ownership. Regular on-site lab work includes server racking, system bring-up, hardware troubleshooting, and documentation.

Designs and maintains large-scale production infrastructure across Linux, Windows, VMware, OpenStack, Docker, and Kubernetes environments. The role administers bare-metal servers and virtual machines, develops automation using Python, Go, and PowerShell, troubleshoots hardware and virtualization issues, and supports incident response through an on-call rotation. Responsibilities also include technical architecture, networking, configuration management, documentation, post-mortems, and applying AI tools to improve operational workflows.