Top Hybrid Jobs in Seattle, WA

Design and develop scalable AI architectures, ML frameworks, algorithms, and production systems for enterprise SaaS. Lead model deployment, monitoring, optimization, and ML platform strategy across the organization. Collaborate with research scientists, product managers, and engineering teams; document technical decisions, conduct code reviews, mentor engineers, and guide adoption of modern AI technologies and responsible ML practices.

Manages and grows a portfolio of local advertising clients by prospecting, developing consultative relationships, and achieving revenue targets. Designs data-informed media strategies across linear TV, streaming, and digital channels; presents proposals; coordinates campaign execution; monitors performance and attribution insights; and maintains forecasts, reporting, and pipeline tracking. The role requires effective objection handling, client relationship management, independent judgment, and availability for nights, weekends, variable schedules, and overtime.

Design, implement, and optimize MongoDB database integrations, Change Data Capture and streaming capabilities, and observability systems. Develop high-performance C++ services, contribute to query engine and distributed systems architecture, lead projects from design through production support, and collaborate with product and engineering teams on technical roadmaps.

Lead and build Pfizer's AI-first design system across human and agent surfaces. Ship design standards-as-code, own conversational and agentic UX, drive adoption metrics, produce high-fidelity prototypes, advise executives, partner with AI/Product/Engineering, and grow a high-performing design team focused on safety, compliance, accessibility, and measurable experience outcomes.

Guide SMB and mid-market sellers through onboarding and implementation, including scoping calls, training, product guidance, launch readiness, and post-launch support. Manage 20–30 concurrent seller engagements, track milestones, resolve blockers, escalate technical issues, and contribute to process improvements. Maintain product expertise across POS, online, and integrations while collaborating with sales, account management, product, and marketing teams. Use AI tools to improve seller experiences and internal processes.

Own the full enterprise sales cycle for Block’s commerce and payments products, from account strategy and prospecting through negotiation, launch, and expansion. Build executive relationships, develop strategic sales narratives, negotiate complex agreements, coordinate cross-functional deal teams, and deliver revenue targets. The role requires strong enterprise selling, commercial strategy, financial analysis, stakeholder management, and familiarity with payments, fintech, digital commerce, or consumer technology.

The Product Security Engineer secures Superhuman’s products and AI systems across the software development lifecycle. Responsibilities include threat modeling, design reviews, secure code reviews, manual testing, vulnerability mitigation, security tooling and automation, bug bounty program improvements, and AI-based security tools. The role partners with engineering teams, communicates security risks and trade-offs, and helps establish secure-by-default platforms and identity models.

Leads the vision, strategy, roadmap, discovery, experimentation, and development of complex innovation products. Identifies customer and business opportunities, translates emerging technologies into product strategies, partners with engineering and design, evaluates prototypes and experiments, manages roadmaps and metrics, and recommends scaling or discontinuing initiatives. Builds relationships across business functions and with external technology partners while creating executive-ready narratives and mentoring product peers.

Leads and scales multiple software engineering teams building DigitalOcean’s distributed compute control plane and orchestration services. Owns multi-quarter technical roadmaps, architectural standards, operational rigor, telemetry, SLOs, resource allocation, and cross-functional delivery. Guides Go microservices development, reduces technical debt, improves platform reliability and scalability, and fosters inclusive, high-performing engineering cultures.

Design and build MLOps infrastructure for production deployment of data, machine-learning models, and software. Develop end-to-end ML pipelines, CI/CD/CT workflows, secure repository strategies, containerized deployments, and automation for Edge AI applications. Collaborate with developers, data scientists, and ML engineers to define tooling, monitor DevOps performance, and improve operational efficiency. Support embedded-system CI/CT, open-source pipelines, and model testing.