Top Remote Senior Level Jobs in Phoenix, AZ

Build and ship production AI systems across retrieval, knowledge graphs, inference, agentic workflows, and data platforms. Develop customer-context retrieval, scored signals, evaluation and observability capabilities, and workflows that turn insights into action. Work hands-on with large and small models, durable orchestration, cloud deployment, inference-cost optimization, and high-volume observability data. Establish reusable engineering patterns, collaborate with product and platform teams, and mentor through strong technical contributions.

Design, build, and operate high-throughput, low-latency ad-serving infrastructure processing millions of requests per second. Optimize GPU-powered TensorRT inference, feature stores, model serving, benchmarking, experimentation tooling, and system reliability. Partner with machine learning engineers to productionize models and own systems through design, deployment, observability, capacity planning, incident response, and optimization.

Design and scale data pipelines and ML/LLM systems, build agentic automation for pipeline generation and maintenance, improve data monitoring, and collaborate with analysts, product, and ML teams to deliver reliable end-to-end data and AI infrastructure for a high-growth e-commerce platform.

Build and deploy production-grade agentic workflows for enterprise customers using Webflow APIs, CMS, AI capabilities, and external integrations. Design safeguards, observability, rollback paths, and permission boundaries; support live web properties at scale; collaborate with sales and engineering on complex deployments; and convert customer implementation learnings into reusable architecture blueprints and platform improvements.

Own and scale strategic relationships with systems integrators and enterprise audit firms. Drive partner-sourced revenue, co-selling, partner enablement, onboarding, forecasting, and executive engagement. Advocate for Drata products, improve audit experiences, coordinate with Sales, Marketing, Product, Engineering, and Customer Success, and help shape the broader alliance ecosystem strategy.

The Enterprise Account Executive will drive enterprise sales of the Qualtrics Experience Management platform, engage with Fortune 100/500 clients, and consistently meet sales quotas while managing relationships.

Leads the development and ownership of Cedar’s production machine learning personalization engine. Responsibilities include ML modeling, MLOps, feature pipelines, deployment, inference, monitoring, feedback-loop optimization, compliance and fairness guardrails, technical leadership, code reviews, cross-functional collaboration, and management of ML engineers. The role requires hands-on contributions to scalable ML systems serving millions of healthcare transactions while guiding roadmap execution and model improvement.

Own the full technology partner lifecycle, from qualification and commercial agreement through integration, activation, joint go-to-market, and royalty revenue generation. Manage a partner territory, forecast performance, conduct QBRs, coordinate with Product, Engineering, and Marketing, and build scalable onboarding and activation playbooks. The role requires enterprise SaaS partner management, commercial negotiation, partner economics expertise, technical fluency, and experience driving integrations and marketplace distribution.

Leads enterprise sales and strategic customer relationships for RigUp’s downstream energy solutions. Responsibilities include prospecting, pipeline management, proposals, negotiations, onboarding, account growth, market development, and cross-functional coordination with Operations, Product, Marketing, and Leadership. The role requires deep downstream oil and gas expertise, C-suite relationship development, complex RFP ownership, frequent client travel, AI-enabled sales workflows, and mentorship of account team members.

Leads Learning, Content, and Quality teams within Shared Services. Owns the strategic vision, operating models, onboarding curriculum, train-the-trainer programs, knowledge bases, quality processes, performance metrics, and AI enablement strategy. The role develops high-performing teams, reduces frontline ramp time and turnover, creates closed-loop feedback systems, and aligns training outcomes with operational KPIs while scaling support operations.