Lead enterprise AI transformation and infrastructure optimization initiatives. Define AI strategy, oversee machine learning models and pipelines, integrate AI into cloud workflows, drive automation, and lead cross-functional AI and engineering teams, including agentic AI initiatives.
This is a remote position.
Lead AI-driven transformation and infrastructure optimization initiatives, integrating machine learning capabilities into enterprise systems.
- Define AI strategy aligned with business objectives
- Oversee implementation of ML models and AI pipelines
- Integrate AI into cloud infrastructure and workflows
- Drive automation and data-driven optimization
- Lead cross-functional AI and engineering teams
- Agentic AI
- 8–15 years experience in AI/ML and infrastructure
- Strong experience in ML models, data pipelines, and cloud platforms
- Experience leading AI transformation projects
Machine Learning | AI Strategy | Data Pipelines | Cloud Integration
Similar Jobs
Fintech • Financial Services
Leads enterprise testing strategy and governance for AI-powered contact center and digital solutions. Oversees UAT, validation, risk assessment, release readiness, defect management, testing metrics, automation, and operational adoption. Coordinates cross-functional stakeholders, SMEs, analysts, business partners, and third parties while managing resources and resolving delivery issues. Establishes scalable controls, procedures, and repeatable testing practices across conversational AI, IVR, routing, telephony, CRM, and integrated data solutions.
Top Skills:
APIsCi/CdCloud PlatformsConversational AiCRMCyaraGithub CopilotHammerIvrJIRAOctaneOmnichannelPlaywrightPythonSoftphoneTelephony
Fintech • Financial Services
Lead enterprise testing strategy and governance for AI-powered contact center and digital solutions. Oversee UAT, validation, defect management, release readiness, risk controls, automation, testing metrics, and stakeholder alignment across business and technology teams. Coordinate testing resources, improve operating models, support adoption decisions, and mentor junior team members while ensuring reliable conversational AI, IVR, routing, telephony, and CRM implementations.
Top Skills:
APIsCi/CdCloud PlatformsConversational AiCyaraGithub CopilotHammerIvrJIRAOctaneOmnichannelPlaywrightPythonSoftphoneTelephony
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Lead the design and hands-on development of an enterprise AI/ML lifecycle governance platform. Build integrations connecting intake, governance gating, routing, observability, monitoring, alerting, feedback, and containment. Define data flows and technical contracts, develop production-grade Python services, implement automated testing, and guide cross-functional engineering teams. The role also evaluates cloud-native platforms, AI observability, governance automation, and responsible AI practices.
Top Skills:
AWSAzureDockerGCPKubernetesPython
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
