Top Remote Jobs in Portland, OR

Build and operate production AI capabilities using Python, LLMs, retrieval, and intelligent automation. Responsibilities include integrating LLM APIs, developing retrieval-augmented features, creating evaluation and prompt frameworks, applying security and compliance controls, monitoring production systems, and collaborating across engineering, data, security, product, and operations teams.

Build and maintain Plane’s cross-platform Flutter mobile app, owning features from interface through data and native integrations. Work on widgets, notifications, webview-based editing, caching, persistence, and compatibility across multiple server versions. Collaborate with backend, design, product, and QA teams while writing tests and maintaining consistent architecture. The role requires production Flutter experience, clean architecture, Bloc-based state management, dependency injection, unit and widget testing, and familiarity with native Android and iOS development.

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.

Owns Xint’s technical content and developer relations strategy for application security practitioners. Conducts and publishes original security research, creates technical tutorials and demonstrations, supports conference talks and webinars, and engages practitioner communities. The role requires hands-on understanding of vulnerabilities, exploit reproduction, security tooling, and AI-assisted security, along with strong technical communication and public speaking skills.

Build and deploy production generative AI systems for Typeform, including LLM applications, RAG, agentic workflows, APIs, machine learning pipelines, and evaluation systems. Design scalable infrastructure using Python, AWS, Docker, Kubernetes, Kafka, Airflow, and MLflow. Improve AI quality, reliability, security, performance, and cost through automated evaluation, monitoring, safeguards, and standardized engineering practices. Collaborate with Product, Engineering, Data Science, Data Engineering, and Analytics teams.

Lead technical enablement for resellers, distributors, MSSPs, and system integrators. Train partner teams, support partner-led sales, run demos and proofs of concept, create technical enablement assets, answer security reviews and RFPs, and provide product feedback. Collaborate with Channel Sales, Sales Engineering, Product, Marketing, and Engineering while representing the company at partner events and customer briefings. Travel is required for partner and customer engagements.

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.

Own and build Nymbus’s global talent acquisition function, including the Greenhouse ATS, recruiting technology stack, AI assessments, dashboards, metrics, employer brand, candidate experience, vendors, and contractor relationships. Lead full-cycle recruiting for technical and specialized roles, partner with executives and hiring leaders, establish scalable processes, and develop AI-forward talent strategies. This remote-first role requires global recruitment expertise, technical fluency, analytical judgment, and independent cross-functional leadership.

Reviews eLearning deliverables for grammar, formatting, functionality, accessibility, audio quality, assessments, and client standards. Tests navigation, interactions, links, branching logic, screen-reader compatibility, keyboard navigation, captions, transcripts, and color contrast. Documents findings, communicates actionable feedback, participates in review cycles, verifies remediation, and retests resolved issues before final approval.

Leads enterprise security reviews, threat modeling, architecture assessments, governance, and control development for AI, generative AI, machine learning, LLM, RAG, and AI-agent solutions. Defines security standards and guardrails, evaluates platforms and vendors, advises cross-functional stakeholders, and supports responsible AI adoption while managing cybersecurity, privacy, regulatory, and operational risks.