Top Remote Automation Engineer Jobs

Contribute to building and hardening micro-apps and AI integrations on a shared GCP platform. Complete bug fixes and small features, participate in code and design reviews, apply security and software development best practices, monitor applications and follow runbooks, and use AI tools to assist development, testing, and documentation while learning from senior engineers.

Lead architecture and delivery of IT automations and integrations across platforms (n8n, Airflow, Temporal, Jira). Act as technical DRI for complex automation projects, partner with Security and IAM, build reusable frameworks and documentation, establish engineering standards and code review practices, and mentor peers.

Build and deploy production micro-apps and LLM-powered agents on a governed GCP platform. Integrate AI with systems (Salesforce, Slack, NetSuite, SQL), harden apps with auth, secrets, CI/CD, logging and monitoring, automate maintenance, and implement evaluation and observability for model quality and drift.

Design, build, and maintain Airflow-based automation pipelines and services to move files, run scheduled FTP jobs, validate and modify data, monitor application health, parse logs/emails, implement robust error handling and observability, and integrate API-driven systems to reduce manual operational work.

Design, implement, and operate CI/CD pipelines for mobile and backend services; maintain build/test/release processes with quality gates and artifact management; configure non-production environments; support release preparation and deployment coordination; integrate monitoring/logging and improve automation, performance, and reliability of delivery pipelines.

Architect and build production agentic AI systems for customer support and compliance automation. Lead technical direction for distributed systems, APIs, orchestration frameworks, guardrails, and evaluation systems. Create reusable automation primitives, improve grounding and reliability, reduce hallucinations, and mentor engineers on LLM application design and production readiness. Collaborate cross-functionally to scale AI automation across Coinbase.

Owns process and automation strategy for optical product manufacturing, including fiber attach, optical alignment, equipment selection, and manufacturing readiness. Drives design-for-manufacturing and cost, develops scalable processes, improves yield and cycle time, qualifies capital equipment, collaborates with suppliers and contract manufacturers, and transfers validated processes and equipment from NPI into production.

Lead QA Automation Engineer to architect and maintain scalable test automation frameworks for web, API, and database layers; define automation, regression, performance, and release testing strategies; write and run automated API/UI/integration/regression/performance tests; integrate tests into CI/CD; own QA backlog, mentor engineers, troubleshoot complex defects, and collaborate cross-functionally to ensure release readiness and quality standards.

Design and implement AI systems for customer support and compliance, architect solutions, mentor team members, and manage project deliverables.

Automate accounting and finance workflows across business systems, data exports, reports, and operational data sources. Responsibilities include improving reconciliations, journal-entry preparation, close tracking, reporting, exception management, and controls; building scripts, dashboards, templates, and workflows; connecting systems; documenting processes; and collaborating with accounting, finance, operations, and technology teams.

Build and launch AI-powered prospecting agents, SDR tools, lifecycle automations, onboarding flows, and internal products. Integrate CRM, sales, and marketing platforms using workflow tools, APIs, scripts, and LLMs. Own lead scoring, routing, SDR-to-AE handoffs, and lifecycle optimization. Measure impact on pipeline, meetings, activation, retention, and CAC payback while partnering with Sales, Lifecycle, Data, and Engineering teams.

Build and operate enterprise container services using Docker and Kubernetes. Create architecture models, technical documentation, and data flow diagrams; coordinate SDLC activities; estimate technical work; apply best practices across development, testing, and deployment; manage Git-based source code; support Agile teams; and improve operational procedures and controls.

Designs, builds, tests, deploys, and supports AI-enabled workflows and business process automations across Business Applications, Data & Analytics, and IT. Evaluates automation opportunities, integrates enterprise platforms through APIs and workflow tools, manages exceptions and human escalation, documents solutions, trains process owners, and reports measurable efficiency gains. The role also monitors emerging AI capabilities, applies governance and security practices, and manages work independently through production release.

Partners with enterprise and MSP customers to identify network automation opportunities, analyze network environments and ITSM data, and architect automation solutions using NetBrain Runbooks, Qapps, Dataviews, and integrations. Trains customer engineers to maintain and expand automation capabilities, collaborates with vendor partners, researches automation content, and delivers reliable troubleshooting and network operations solutions.

Lead hands-on engineer designing and modernizing cloud-native, reliable, and automated software solutions. Drive adoption of enterprise AI-assisted engineering practices, build automation frameworks, support performance and resiliency testing, lead code reviews, and communicate technical strategy and reliability standards across teams.

Own and operate a global, multi-vendor production network: configure and troubleshoot routers/switches, manage BGP peering and transit, maintain firewalls and load balancers, monitor network health, perform packet captures and root-cause analysis, execute software upgrades with minimal disruption, build monitoring/visibility tools, and document runbooks and post-incident reports to ensure high availability for a SaaS platform.

Build autonomous AI agents and infrastructure for security, compliance, and risk programs. Design agent workflows, MCP integrations, ETL and agentic data pipelines, data lakehouse solutions, and secure data-access systems. Monitor and optimize production agents and data infrastructure, ensure privacy and governance, translate business needs into scalable solutions, and mentor engineers on data engineering and agent-native design.

Hands-on technical leader who designs, builds, and deploys production-grade AI automation and agentic workflows. Responsibilities include rapid prototyping, RAG and document-intelligence systems, API integrations, orchestration, monitoring, reusable AI assets, and mentoring a small engineering team to deliver frequent releases and measurable business impact.

Designs and deploys AI assistants, copilots, custom agents, and end-to-end workflow automations across business functions. Builds integrations between AI platforms and enterprise systems using APIs, middleware, and serverless architectures. Develops prompt, RAG, and agentic solutions while measuring ROI and adoption. Partners with IT Operations and Security on governance, privacy, compliance, and secure deployment. Documents solutions, trains teams, and continuously improves automations based on usage and feedback.

Design, build, and deploy Tier Zero self-service solutions (virtual agents, chatbots, automated troubleshooting), intelligent routing, and predictive maintenance. Integrate automation with ITSM platforms, use low-code/pro-code tools (e.g., Power Automate), track deflection and satisfaction metrics, ensure accessibility compliance, document architectures and runbooks, and coordinate with service desk and cloud teams to drive continuous improvement.

Build and maintain internal and customer-facing web/cloud apps and AI automations. Integrate with third-party APIs (QuickBooks, Microsoft Graph, Zoho, Zoom), implement generative-AI features, ensure security, deploy to cloud, and collaborate with leadership and IT. Work independently on design, testing, and maintenance across varied projects.

Build and maintain cloud- and browser-based AI and automation applications (internal and customer-facing). Integrate with third-party APIs (QuickBooks, Microsoft Graph, CRM, Zoom), implement AI workflows (OpenAI), automate business processes (Zoho, PowerAutomate), and ensure security and maintainability while working closely with leadership and IT.

Design and deliver LLM-powered, agentic AI systems to automate customer support and compliance. Build scalable, secure backend infrastructure in Python and Go, integrate third-party models/APIs, implement grounding and guardrails, and measure performance. Lead end-to-end projects, mentor engineers, conduct code reviews, and participate in on-call and incident response to improve resolution times and reduce operational costs.

Build and maintain Unreal Engine 5 tools and development infrastructure, including crash reporting, diagnostics, telemetry, automated testing, CI workflows, editor utilities, command-line tools, and validation systems. Integrate tools with source control, build systems, issue tracking, external services, and platform workflows. Investigate failures, improve debugging and triage processes, collaborate across engineering and production teams, and document maintainable solutions.

The Automation Developer will create, maintain, and scale automated test coverage for UI, API, and integration layers, utilizing various tools and scripting skills.