Top Remote Python Jobs in Washington, DC

Own Telnyx’s global phone-number ordering pipeline, carrier integrations, regulatory automation, AI-powered order review, and Postgres data layer. Build reliable async Python services with retries, rollbacks, queues, SLA monitoring, document verification, auditability, and human escalation. Improve automation across dozens of vendors and 45+ countries while maintaining dashboards, analytics, and operational alerts across a large microservice estate.

Designs, deploys, and manages secure, scalable AWS infrastructure using Terraform, CloudFormation, containers, and Kubernetes. Builds CI/CD pipelines, implements cloud security controls, monitors performance and costs, troubleshoots infrastructure and deployment issues, and supports high availability and disaster recovery. Collaborates with development and operations teams to deliver reliable cloud solutions for a Department of Veterans Affairs project.

Designs and delivers Amazon Connect and Salesforce contact center solutions for enterprise customers. Leads discovery, technology assessments, ROI development, architecture, integrations, and cloud deployment discussions. Translates business requirements into contact center designs, oversees technical teams, manages stakeholder communications, and ensures projects meet quality, budget, and timeline goals. Provides customer training and documentation while guiding cloud infrastructure, automation, monitoring, security, and compliance practices.

As an AWS Solution Architect, you'll design and implement Amazon Connect solutions, improve customer processes, lead technical teams, and educate clients on AWS value.

Leads and develops a team of 4–6 software engineers building and operating React Native mobile applications, backend services, and administration platforms. Responsibilities include people management, architecture, code quality, technical debt reduction, delivery planning, cross-team collaboration, infrastructure and security coordination, engineering metrics, and rotating on-call support. The role remains technically engaged through design reviews, coding, troubleshooting, and architectural guidance.

Leads a team responsible for hardware-in-the-loop verification and validation of autonomous trucks. Owns HiL strategy, roadmap, test campaigns, bench development, requirements traceability, safety compliance, defect triage, and V&V reporting. Partners with product, systems, safety, tools, and external vendor teams. Guides testing aligned with ISO 26262 and ISO 21448, including fault handling, safety mechanisms, autonomous driving systems, and performance limitations.

Builds and operates AWS developer-platform infrastructure, CI/CD pipelines, Terraform-based service infrastructure, Kubernetes and serverless workloads, and self-service onboarding workflows. Responsibilities include configuring connectivity, secrets, observability, security controls, and environment promotion; troubleshooting delivery and production issues; supporting releases; managing infrastructure drift; and contributing to AI-augmented automation and tooling. The role partners with Engineering, Release, SRE, and Infrastructure teams while maintaining documentation and compliance evidence.

The Senior IT QA Engineer owns quality strategy and outcomes across complex technology initiatives. Responsibilities include designing automated testing solutions, integrating quality verification into CI/CD pipelines, analyzing quality and production data, developing dashboards, managing risk, leading root-cause analysis, and influencing product, engineering, architecture, security, operations, and business stakeholders. The role requires technical contributions across web, mobile, API, data, cloud, and distributed systems, plus mentoring engineers and advancing quality engineering practices.

Own system-level testing for Lance and LanceDB across correctness, reliability, scalability, performance, data integrity, fault recovery, upgrades, and compatibility. Build automated test frameworks, realistic workloads, fault-injection scenarios, performance and soak tests, and reproducible CI environments. Investigate failures using logs, metrics, traces, and source code, create minimal reproductions, and partner with engineers on fixes. Apply AI tools responsibly to accelerate test development, failure analysis, and debugging.

Lead the design, development, reliability, scalability, and operational excellence of Humana’s Next Best Action platform. Build platform services, automated testing, observability, resilience, and production-readiness capabilities across distributed systems. Write production code, manage and mentor engineers and contractors, establish quality standards, and coordinate with platform, data, decisioning, orchestration, and activation teams. Ensure high performance, traceability, fault tolerance, and compliance in a regulated healthcare environment.

Designs, automates, and improves the reliability, availability, and recoverability of on-premises, hybrid, and cloud technology platforms. Builds infrastructure-as-code, recovery workflows, self-healing systems, monitoring, and validation processes; defines resiliency objectives; conducts disaster recovery tests and chaos experiments; and facilitates architecture reviews and recovery exercises. Partners across engineering, infrastructure, cloud, application, and business teams while maintaining regulatory-ready documentation.

Lead the architecture, security, and operation of Maestro’s multi-tenant AI platform on private GKE. Build Kubernetes operators, isolated per-user runtimes, identity and credential systems, service-mesh security, Terraform infrastructure, CI/CD, observability, audit pipelines, fleet operations, and human approval guardrails. Partner on safe agent integrations, establish platform and security standards, mentor engineers, and guide infrastructure strategy as the system scales.

Build and operate an AI-native platform spanning Kubernetes, infrastructure as code, CI/CD, identity, networking, security, compliance, observability, and cost management. Develop reusable platform modules, delivery pipelines, policy gates, isolated client environments, and AI development tooling. Lead through hands-on engineering, architecture decisions, design reviews, migrations, documentation, and developer enablement while ensuring reliability, security, and measurable developer outcomes.

Build and own automated testing frameworks, CI/CD infrastructure, load and stress testing, and chaos engineering practices for a brokerage platform. Write primarily Go, integrate AI and LLM tooling into quality workflows, investigate application and Kubernetes failures, improve developer tooling, and mentor engineers on reliability and test coverage.

Build and architect Alpaca’s algorithmic trading platform, developing high-performance, low-latency brokerage systems. Responsibilities include extensive frontend and backend coding, distributed system design, database and concurrency architecture, high availability, throughput optimization, and object-oriented modeling. The role requires prior experience with trading or exchange systems, including OMS and RMS platforms, and involves making critical technical decisions in a demanding early-stage environment.

Design, tune, model, validate, and deploy classical and advanced control systems on physical hardware such as robotics, drones, automotive, and industrial systems. Develop plant models, implement control algorithms in Python and open-source tools, analyze performance, document decisions, and collaborate remotely with interdisciplinary teams.

Design, simulate, verify, and validate analog, digital, power, mixed-signal, or RF circuits for an AI training project. Translate requirements into schematics, netlists, HDL, models, and simulation inputs; automate workflows with Python; analyze electrical results; perform corner and Monte Carlo analyses; compare simulations with physical measurements; troubleshoot hardware and review AI-generated circuit solutions. Requires real fabricated or shipped circuit-design experience and command-line or programmatic EDA expertise.

Build and maintain AI-assisted full-stack platforms for manufacturing, spanning AWS infrastructure, Python Lambda services, Java microservices, agentic LLM workflows, and Angular interfaces. Develop event-driven architectures, APIs, retrieval and scoring systems, infrastructure as code, observability, CI/CD, and secure deployment strategies. Apply rigorous testing, specification-driven development, concurrency practices, and production reliability techniques across multi-repository systems. The role requires hands-on software development experience with enterprise server, storage, or networking products.

Designs, builds, and operates observability and SRE systems that improve IT service visibility, reliability, performance, and resilience. Responsibilities include metrics collection, monitoring, alerting, APM, RUM, synthetic transactions, SLOs, incident response, capacity planning, infrastructure automation, self-healing systems, and production readiness reviews. The role also applies AI-enabled operations, supports on-call rotations, reduces operational toil, and partners with development teams on architecture and chaos testing.

Build and govern reliable, scalable production infrastructure across cloud environments. Responsibilities include DevOps guardrails, CI/CD, Terraform-based infrastructure, deployment strategies, developer platforms, observability, SLOs, incident response, capacity planning, automation, chaos engineering, and cloud optimization. The role partners with engineering teams to improve resilience and supports .NET services across Windows and Linux.

Build shared automation frameworks, developer tools, and quality engineering platforms. Develop API, application, platform, AI, and security testing; integrate quality checks into CI/CD; investigate failures; evaluate AI-assisted testing; and mentor teams while driving adoption of reusable testing practices.

Lead design and implementation of Azure full‑stack, scalable skilling platform features. Drive CI/CD, reliability, automation, and AI/LLM-enabled capabilities. Mentor engineers, enforce engineering best practices, coordinate cross-team dependencies, and improve test automation and observability for enterprise-scale services.

Design, build, and optimize production-grade applications on Azure while contributing to an observability-focused Azure service. Responsibilities include developing cloud-native systems, creating reusable engineering assets, supporting production environments through on-call participation, investigating incidents, improving reliability and performance, and influencing Azure platform engineering through customer insights. The role also involves direct engagement with strategic customers and strengthening technical capabilities across the organization.

Design and scale production-grade asynchronous backend systems in Python, including REST/WebSocket APIs, multi-agent LLM workflows, provider-agnostic integrations, and RAG pipelines. Build schemas and migrations, optimize relational databases, instrument services, and own CI/CD from testing through deployment. Establish AI governance around code review, provenance, licensing, security, compliance, and customer data. Drive architecture and product ideas from conception through production.

Leads QA strategy and test architecture for Kubernetes, cloud-native, distributed, and multi-cloud systems. Designs scalable automation, production-like test scenarios, chaos and performance testing, CI/CD quality gates, and infrastructure-as-code. Provides technical leadership through risk analysis, release readiness assessments, incident retrospectives, architecture reviews, and mentorship. Requires deep Kubernetes, Linux, cloud, automation, observability, security, and troubleshooting expertise.