Top Remote Engineering Jobs

Lead a software engineering team building and operating Snorkel AI’s platform in government and regulated cloud environments. Define architecture, deploy services, establish infrastructure-as-code and CI/CD workflows, and ensure security, monitoring, vulnerability management, incident response, compliance, and auditability. Partner with platform, security, compliance, product, and applied AI teams while hiring, coaching, and developing engineers and setting technical standards.

The Head of Engineering will drive technical direction, develop product architecture, and eventually lead the engineering team while coding and building AI systems.

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.

Research and analyze rendering algorithms, translate graphics concepts into computationally efficient models, conduct competitive and performance benchmarking, and collaborate with hardware architects to define proof-of-concept features and system requirements. The role focuses on graphics processors, hardware-based ray tracing, performance modeling, and communicating technical findings to leadership.

Designs, builds, deploys, and maintains secure full-stack identity governance software for federal customers. Responsibilities include backend and frontend development, distributed systems architecture, cloud and on-premises infrastructure, CI/CD, observability, reliability, audit readiness, and operations in disconnected or classified environments. The role also requires collaboration across engineering, product, and design; architectural leadership; AI-augmented software development; and mentoring peer engineers.

Design and maintain automated testing frameworks for web, iOS, and Android fitness applications. Integrate tests into CI/CD pipelines, build API coverage, test GPS and location features through simulation and sensor mocking, and use AI tools to improve QA workflows. Perform targeted exploratory testing, document defects, collaborate cross-functionally, estimate QA work, and advocate for quality throughout development.

Design, deploy, administer, secure, monitor, and troubleshoot enterprise AWS cloud infrastructure. Automate provisioning and operational workflows using IaC, scripting, Git, and DevOps practices. Support Windows and Linux environments, virtualization, containers, networking, monitoring, auditing, cost optimization, and complex application infrastructure. Use AI-assisted tools and LLMs for engineering productivity, maintain technical documentation, and participate in occasional after-hours maintenance and onsite activities.

Leads and mentors application engineers while designing Java and Spring Boot microservices. Oversees application modernization, VM-to-container migration, GCP and GKE deployments, Kubernetes troubleshooting, CI/CD, testing, database integration, observability, and distributed systems. Coordinates technical dependencies across a large application portfolio and collaborates with platform, DevOps, security, and architecture teams. Uses AI-assisted engineering tools to accelerate development, modernization, testing, documentation, and automation.

Build and scale full-stack software for an AI-native cybersecurity platform. Responsibilities include developing backend services and APIs, creating frontend applications, collaborating on product features, writing tested code, participating in reviews, troubleshooting across the stack, and improving engineering processes. The role requires 3–5 years of software engineering experience and experience with backend, frontend, databases, and cloud technologies. Docker, Kubernetes, CI/CD, AI/ML, and startup experience are preferred.

Serves as a principal technical leader across Integrations, Workflows and Orchestration, and Data Management. Designs and modernizes distributed, event-driven backend systems; writes production code; resolves reliability issues; leads incident response; establishes engineering practices; shapes technical roadmaps; evaluates build-versus-buy decisions; documents architecture; mentors engineers; and influences teams and stakeholders without direct authority.