Top Remote Python Jobs in Washington, DC

Administer and optimize ArcGIS Enterprise environments, including geospatial services, datasets, upgrades, monitoring, performance tuning, automation, and cloud modernization. The role supports ArcGIS Enterprise on Amazon EKS, automates service publication and data workflows, conducts load testing and capacity planning, troubleshoots platform issues, and maintains technical and change-management documentation in a federal government environment.

Develop and execute comprehensive tests for GIS applications, ArcGIS tools, geospatial workflows, automated validation processes, and web mapping applications. Validate spatial data, geodatabase attributes, Real Property records, business rules, reports, dashboards, and integrations using SQL and scripting. Document defects, investigate root causes, verify fixes, and collaborate with GIS specialists, developers, and analysts. The role requires Esri GIS, Army Real Property and IGI&S knowledge, automated testing experience, and CAC eligibility.

Design, commission, operate, troubleshoot, and improve industrial automation and control systems for Hertha Metals’ ironmaking process. Responsibilities include PLC and HMI programming, control strategy development, FAT/SAT, plant commissioning, loop tuning, alarm and historian management, root cause analysis, safety reviews, and on-site operational support. The engineer will collaborate with process, mechanical, electrical, operations, maintenance, vendors, and system integrators during plant scale-up and future facility expansions.

Supports the design, installation, commissioning, operation, troubleshooting, and continuous improvement of industrial instrumentation, control, and electrical systems for a steelmaking plant. Responsibilities include developing engineering documentation, supporting start-ups and maintenance programs, conducting root cause analyses, ensuring code and safety compliance, participating in HAZOPs and safety reviews, and collaborating with operations, contractors, vendors, and engineering teams during plant scale-up.

Administer and optimize Oracle databases across AWS RDS GovCloud and on-premises environments. Responsibilities include upgrades, patching, backup and recovery, performance monitoring, SQL and PL/SQL troubleshooting, database security, Linux and Windows administration, RMF and DISA STIG compliance, audit evidence, vulnerability remediation, release support, and technical documentation. The role requires customer communication, independent problem-solving, and occasional after-hours support and travel.

Lead end-to-end technical ownership for an e-commerce platform service area. Design, build, and ship production features; modernize legacy systems; establish architecture and engineering standards; optimize platform performance; plan roadmaps and sprint priorities; mentor engineers; improve developer productivity; and contribute to hiring. The role requires hands-on TypeScript, JavaScript, React, Node.js, AWS, Python, and Django experience in a remote United States or Canada environment.

Build and maintain backend product features using Python, Django, and relational databases. Develop APIs, asynchronous jobs, integrations, internal tools, and data-processing workflows while using and critically reviewing AI-generated code. Investigate incidents, resolve customer-impacting issues, improve reliability and database performance, and protect data integrity, security, tenant isolation, and auditability. Own work through testing, deployment verification, documentation, and follow-up while collaborating closely on a small engineering team.

Develop and improve LLVM/Clang-based compiler infrastructure for Arm microcontrollers and proprietary DSPs. Collaborate with application, architecture, design, and engineering teams to enhance compiler performance and support architectural improvements. Work under mentorship while applying software development, debugging, performance analysis, testing, compiler design, and computer architecture knowledge.

Owns enterprise source control and release engineering strategy, consolidating Git platforms and standardizing secure CI/CD workflows. Administers GitLab and GitHub, builds pipelines, and operates shared container registry, object storage, and secrets-management services. Develops infrastructure as code with Terraform or CloudFormation and automation using Python, PowerShell, and Bash. Supports Docker and Kubernetes workflows, security scanning, observability, compliance, documentation, and cross-functional platform governance.

Senior Full Stack Engineer responsible for taking over an existing software project, completing unfinished features, resolving bugs, improving frontend and backend systems, integrating APIs and databases, refactoring for reliability and scalability, and preparing the application for production. The role requires independent ownership, strong debugging and software development skills, collaboration with stakeholders, automated testing, deployment workflows, and clear technical documentation.

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.

Senior Python Developer responsible for taking ownership of an existing software project, understanding its architecture, completing unfinished features, resolving bugs, reducing technical debt, improving performance and reliability, expanding test coverage, and preparing the application for production release. The role requires independent decision-making, collaboration with stakeholders, API and database integration experience, and strong software engineering practices.

Owns reliability, availability, incident response, and infrastructure for a regulated SaaS platform. Maintains AWS and Azure environments using Terraform, operates Kubernetes production systems, develops automation, improves observability and deployment safety, mentors engineers, and helps establish the company’s reliability practice.

Build and operate cloud-native platform infrastructure enabling AI agents in healthcare: safe CI/CD for agent capabilities, agent-focused observability, scalable infrastructure, automation, runbooks, and incident response.

Build and operate large-scale audio data pipelines for AI model training. The role involves discovering data sources, developing reliable data-processing systems, optimizing quality, throughput, and cost, and collaborating with AI scientists. The engineer will own projects from discovery through implementation and ongoing improvement, using strong backend engineering skills in Python, Bash, and Linux environments.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, improving data-processing systems for quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement. The role requires strong backend software engineering skills, production systems experience, and proficiency in Python, Bash, and Linux, with preferred experience in web crawling, distributed processing, GCP, Terraform, and audio or ML training data.

Build large-scale data pipelines and processing systems that produce high-quality audio datasets for AI model training. Discover data sources, optimize throughput, quality, and cost, operate production systems, and collaborate with AI scientists on next-generation models. The role requires strong backend software engineering, independent problem-solving, and ownership of projects from discovery through continuous improvement.

Build and operate large-scale data pipelines for AI training datasets, including discovering audio sources, processing data efficiently, optimizing quality and cost, and collaborating with AI scientists. Own engineering projects from discovery through implementation and continuous improvement. The role requires strong backend software engineering, production systems experience, Python and Bash proficiency, and independent problem-solving in ambiguous environments.

Build and operate large-scale data pipelines that collect audio data for AI training. Responsibilities include discovering data sources, optimizing data-processing systems for quality, 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. Responsibilities include discovering data sources, developing reliable data-processing systems, optimizing data quality, 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. Responsibilities include discovering data sources, developing reliable data-processing systems, optimizing quality, throughput, and cost, and collaborating with AI scientists. The role owns engineering projects end to end and requires strong backend software engineering skills, Python and Bash proficiency, production systems experience, and independent problem-solving.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, developing data-processing systems, optimizing quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement. The role requires strong backend software engineering skills, production systems experience, and independent problem-solving in an ambiguous environment.

Build and optimize petabyte-scale data pipelines for AI model training, including audio data acquisition, large-scale processing, and dataset quality improvements. Collaborate with AI scientists, operate production systems, and independently manage engineering projects from discovery through continuous improvement. The role emphasizes backend software engineering, scalability, throughput, cost efficiency, and reliable infrastructure.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, developing reliable data-processing systems, optimizing quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement.

Build and operate large-scale data pipelines for AI model training, including discovering audio data sources, optimizing data processing for quality, throughput, and cost, and collaborating with AI scientists. Own engineering projects from discovery through implementation and continuous improvement. The role requires strong backend software engineering skills, production systems experience, and independent problem-solving in ambiguous environments.