Top Artificial Intelligence Jobs

Develop and productionize fraud detection machine learning models, engineer features from large-scale behavioral and transaction data, and monitor model performance. Lead complex fraud investigations by reconstructing attacker behavior, identifying patterns, producing technical reports, and translating findings into detection improvements and customer-facing fraud trend insights. Collaborate with product, engineering, operations, legal, executives, and customers.

Onboard and educate B2B customers, host customer calls, identify adoption issues, recommend solutions, and help develop scalable customer success processes. Partner with engineering on tooling and product feedback, create educational content and webinars, and use Pylon internally to improve customer workflows. The role is customer-facing, technical, and based in San Francisco with in-person work.

Own the functionality, integration, performance, and stress-testing roadmap for an AI/ML healthcare platform. Develop automated tests, frameworks, tools, and processes across web, mobile, and backend systems. Investigate testing approaches for AI/ML applications, improve coverage and automation, diagnose bugs, create test plans, refine acceptance criteria, and support the full software lifecycle. Collaborate with engineering, product, design, operations, and release teams while mentoring junior engineers and working independently.

Own 25–40 mid-market customer accounts, leading implementation, integrations, SSO and SCIM setup, admin training, adoption, technical troubleshooting, health monitoring, and customer feedback. Drive successful rollouts and user engagement, independently resolve first-line issues, identify renewal and expansion signals, and coordinate commercial handoffs without owning pricing or renewals.

Support email and SMS lifecycle programs across client accounts: write briefs, build/QA/deploy campaigns and flows in Klaviyo and other ESPs, troubleshoot rendering and integrations, analyze CRM KPIs, manage tasks in the PM system, maintain client files, and advise stakeholders on CRM best practices.

Own go-to-market strategy and launch readiness for Numa’s AI dealership product suite. Develop positioning, messaging, competitive differentiation, target segmentation, sales and customer success enablement, and repeatable launch processes. Partner closely with Product and Engineering, use the product, translate technical AI capabilities for varied audiences, track organizational readiness, and create scripts or automations to improve execution. The role requires strong technical fluency, writing, cross-functional collaboration, and comfort building structure in an evolving environment.

Own the integration layer connecting Spherecast with ERPs, FTP and S3 sources, data warehouses, and custom sheets. Build scalable, fault-tolerant, near-real-time pipelines handling large data volumes; orchestrate syncs; validate, normalize, and upsert data; and implement safe write paths for AI-approved ERP actions. Develop round-trip tests, monitoring, structured logging, alerting, auditability, and reusable connector architecture while working directly with customer operators and IT teams.

Lead business value assessments for enterprise customers, quantifying the financial impact of improved software delivery. Translate customer pain points into ROI and TCO models using validated assumptions and platform data. Create executive-ready business cases and value narratives supporting sales, expansions, and renewals. Partner with Sales, Solutions Engineering, and Customer Success while developing scalable value-selling methodologies, benchmarks, calculators, templates, and enablement.

Partners with Sales and Customer Success teams as a technical expert across the client lifecycle. Scopes expansions, designs solutions, leads discovery, delivers technical demonstrations, supports RFPs, guides website integrations, troubleshoots JavaScript tags, pixels and APIs, and coordinates documentation and handoffs to Implementation and Support.

Own the full accounting lifecycle, including billing, invoicing, revenue recognition, general ledger management, reconciliations, month-end close, GAAP financial reporting, audits, tax filings, and internal controls. Build scalable accounting processes and systems for a fast-growing SaaS business while partnering with Sales, Legal, and Customer Success on contract setup and billing. Serve as a strategic advisor on financial operations and reporting.