Top Remote Python Jobs in Washington, DC

Own full-stack features end to end, including system design, implementation direction, testing, deployment, production operations, and incident response. Use agentic AI to generate code, tests, and reviews while validating quality and security. Build production APIs, data models, authentication, schemas, migrations, and scalable SQL. Collaborate with Product, Design, and DevOps, and apply secure coding practices. Bonus experience includes RAG, LLM evaluation and observability, or TypeScript frontend development.

Design, develop, test, and optimize safe, scalable real-time software for production autonomous vehicle systems. Architect continuous learning infrastructure for ML model deployment and monitoring, analyze algorithms, and collaborate with embedded, platform, AI, sensor, and compute teams. Support perception, prediction, and planning integration while contributing to highway and urban autonomous driving capabilities.

Develop productionized machine learning workflows, cloud infrastructure, distributed data-processing pipelines, and a multi-tenant data lake for autonomous-driving AI. Build internal APIs, CI/CD processes, and developer productivity tools while collaborating with research engineers. The role requires strong software engineering, DevOps, infrastructure-as-code, microservices, networking, and data infrastructure expertise.

Design and implement motion-planning software for autonomous vehicles, including behavior planning, trajectory generation, safety constraints, and real-time embedded performance. Integrate planning with perception, prediction, localization, and control systems. Validate solutions through simulation, closed-course trials, and on-road testing while addressing complex edge cases and collaborating with vendors, AI teams, and customers.

Build and own production software systems spanning embedded systems, real-time control, cloud services, and data pipelines. Responsibilities include architecture, coding, testing, reliability engineering, observability, incident response, technical design reviews, cross-functional hardware collaboration, hiring, and mentoring. The role requires strong systems fundamentals, distributed systems experience, debugging ability, and proficiency in at least one major programming language.

Manage and develop an engineering team while owning delivery, hiring, performance, technical judgment, and escalation response. Stay hands-on with coding and architecture, use coding agents effectively, improve engineering processes, and help engineers build stronger skills in scoping, estimation, decision-making, and ownership. Balance roadmap priorities with customer commitments and turn recurring issues into lasting product improvements across HumanSignal’s AI data and annotation platforms.

Develop and maintain web and AI-based enterprise applications through design, coding, testing, debugging, documentation, and code reviews. Integrate AI-assisted and agentic development tools into engineering workflows, manage context and harness engineering, and mentor teammates on responsible AI use. Collaborate across teams, lead projects and design efforts, improve processes and technology choices, and build secure, scalable services using modern backend stacks, REST APIs, databases, cloud infrastructure, and CI practices.

Designs, builds, and maintains scalable backend services, APIs, databases, data flows, and infrastructure. Leads complex features from design through deployment while improving performance, observability, security, testing, and reliability. Integrates third-party platforms, supports cloud infrastructure and CI/CD practices, and mentors engineers through technical guidance and knowledge sharing.

Designs, implements, and maintains secure integrations between IAM platforms and external systems such as ID.me, ServiceNow, and the ELK Stack. Develops APIs, middleware, data transformations, and iPaaS workflows; configures monitoring and alerting; troubleshoots cross-platform data flows; and ensures secure transmission and federal compliance. The role also produces technical documentation and collaborates with agile teams on development, testing, and deployment.

Provides architectural oversight for complex mainframe software products and mission-critical systems. Designs and validates enterprise architectures, documents components and interfaces, advises technical teams, integrates developer-built components, and communicates with technical, non-technical, and government stakeholders. Requires extensive COBOL and mainframe expertise, healthcare claims and CMS experience, Agile/SAFe knowledge, and ability to obtain Public Trust clearance.

Develop and maintain COBOL-based Medicare claims processing software in a legacy mainframe environment. Responsibilities include designing, coding, debugging, unit testing, implementing enhancements, troubleshooting defects, supporting Agile/Scrum delivery, preparing estimates, maintaining documentation, and collaborating with team members, clients, and vendors. The role supports Durable Medical Equipment claims processing and requires adherence to structured development standards.

Leads global new product introduction activities for optical networking hardware and software, including customer onboarding, demonstrations, lab certifications, test planning, troubleshooting, escalations, and early field trials. Serves as the liaison between customers, support, engineering, testing, and product teams from first customer shipment through general availability. Uses customer feedback to improve serviceability, product quality, adoption, and overall customer experience.

Designs scalable, production-grade architectures for enterprise applications, distributed systems, cloud platforms, APIs, integrations, and data flows. Defines architectural standards, evaluates technology trade-offs, and guides cloud engineering, modernization, CI/CD, infrastructure as code, observability, security, and reliability practices. Provides technical leadership through design reviews, mentoring, client collaboration, solution shaping, and technical planning while supporting scalable and maintainable software delivery.

Design and scale infrastructure for cloud and on-premises deployments supporting enterprise AI workloads. Build containerized systems, Kubernetes and Docker Compose deployments, Helm charts, CI/CD pipelines, infrastructure automation, monitoring, and security solutions. Support customer production deployments, troubleshoot distributed systems, improve developer productivity, mentor engineers, and establish infrastructure standards across engineering teams.

Build and deliver full-stack features for a web-based broker platform, collaborate with product and design, manage technical debt, shape architecture for scalability, participate in code reviews, and adopt AI-powered developer tools.

Leads a large engineering team responsible for scalable customer runtime infrastructure supporting Drupal, WordPress, and Next.js sites. Oversees technical strategy, architecture, project delivery, modernization, operational reliability, mentoring, performance management, and cross-functional collaboration. Guides cloud infrastructure transformation, reviews critical code, manages multiple priorities, and develops a high-performance engineering culture across global teams.

As a Forward Deployed Engineer, you will develop AI agents and automation workflows, collaborate with teams, and ensure secure, reliable solutions integrating with various systems.

Build and own core platform infrastructure, including Terraform, cloud environments, CI/CD pipelines, developer tooling, observability, monitoring, alerting, secrets management, and deployment abstractions. Partner with product engineers to improve delivery speed and reliability, support GCP messaging infrastructure, develop compliance tooling, improve cost visibility, and independently operate production systems in a regulated fintech environment.

Lead the architecture and development of a multi-RAT Open RAN digital twin supporting LTE and 5G NR simulation. Integrate production MAC and scheduler software with PHY, channel, UE, traffic, mobility, interference, and network models. Build fidelity tiers, AI/ML evaluation pipelines, reproducible experiments, calibration and validation practices, automated testing, and CI/CD workflows. Improve simulation scalability and reliability while collaborating across wireless, PHY, AI/ML, software, and lab-validation teams.

Own end-to-end quality for new features across the operator portal, backend platform, and endpoint agent. Translate requirements into runnable acceptance coverage, build and maintain parallel browser test frameworks, validate APIs and contracts, and integrate suites into CI release gates. Curate automated and AI-generated scenarios, assess test risk, report coverage and failures, and close quality gaps. The role also drives adoption of shared tooling and may involve containerized environments, cloud platforms, virtualization, performance testing, and security product testing.

Develop and maintain high-volume, mission-critical enterprise web applications using C#/.NET, ASP.NET MVC, AngularJS, and SQL Server. Responsibilities include full lifecycle development, architecture and design participation, troubleshooting, performance and scalability improvements, AI-assisted workflow development, Agile collaboration, technical mentoring, and supporting multi-tier systems.

Build and improve Replicant’s AI-native platform, including site reliability, CI/CD, developer tooling, observability, incident management, cloud infrastructure, and autonomous-agent harnesses. Own production infrastructure reliability at scale, reduce operational toil, improve deployment workflows, participate in on-call rotation, and shape platform engineering patterns. The role uses TypeScript/Node.js, Python, Terraform, Kubernetes, Helm, GCP, and modern monitoring tools.

Lead end-to-end design, development, deployment, testing, and production support of enterprise web applications. Build scalable client/server architectures, ensure security and data governance, mentor team members, collaborate with product and business stakeholders, and own timely delivery and quality of solutions. Analyze data patterns and support reporting and selection workflows.

Build and improve Replicant’s AI-native platform infrastructure, including site reliability, CI/CD, developer tooling, observability, incident management, and agent harness systems. Own production infrastructure patterns, deployment workflows, and developer self-service across Kubernetes and cloud environments. Participate in on-call and incident response while improving scalability, availability, and operational efficiency for real-time conversational AI traffic.

Designs, develops, and supports enterprise HPC and cloud infrastructure solutions. Responsibilities include architecture, software platform development, proof-of-concept delivery, capacity planning, system design, launch reviews, troubleshooting, documentation, and collaboration with engineering, product, sales, and open-source communities. The role requires maintaining system performance, solving ambiguous technical problems, and participating in an on-call rotation.