Top Artificial Intelligence Jobs

Lead technical vision and architecture for ML-driven trajectory generation in autonomous vehicles. Build and deploy scalable training pipelines, integrate models into real-time safety-critical onboard systems, mentor senior engineers, drive cross-functional initiatives, and move solutions from research to production using simulation and large-scale datasets.

Lead and design emerging-technology projects from concept to prototype, evaluate technologies and business models, run user research and validation, build scorecards, pitch opportunities, present findings, and maintain cross-functional and external partnerships to scale business impact.

Lead product strategy and delivery for Kai, Airwallex's AI assistant. Partner with engineering, design, and cross-functional teams to build scalable LLM-powered features, validate new agentic use cases, balance model quality and cost, and drive product performance using user feedback and production conversation data.

Rapidly prototype and validate AI solutions for advisor workflows: integrate models, signals, and UX into experiments, test feasibility and performance, iterate with user feedback, document technical learnings, and hand off prototypes for productionization.

Lead the design and delivery of AI-driven marketing systems to automate repetitive workflows, build agentic content and reporting pipelines, create a centralized AI-queryable knowledge foundation, and partner cross-functionally to connect data and systems that drive pipeline and revenue outcomes.

Design, build, and deploy production-grade AI applications using LLMs, RAG, and agent architectures. Implement vector-database-backed retrieval solutions, create scalable REST APIs and cloud-native backends, and collaborate with cross-functional teams to translate business requirements into robust AI solutions following engineering best practices.

The Director of AI/ML Engineering will drive AI transformations, manage a large engineering team, ensure project delivery, and influence business strategies in healthcare.

Lead enterprise AI strategy and execution to design, pilot, deploy, and scale generative AI, conversational assistants, agentic automation, and AI-enabled workflows across clinical, product, and enterprise systems in a regulated healthcare environment. Align cross-functional teams, define success metrics, and ensure compliance, auditability, and continuous improvement of production AI capabilities.

Ship full‑stack features end-to-end using AI coding agents, drive architecture and technical direction, collaborate with Product and Design, write scalable maintainable code, mentor engineers, document work, and translate industrial automation customer problems into engineering tasks.

As a Senior AI Engineer, you'll develop ML and Generative AI models, ensure integration with enterprise applications, and manage large datasets while collaborating with teams and mentoring others.

The Senior Product Manager will develop and execute product strategies for AI-driven data products, ensuring alignment with customer needs and business goals while collaborating with engineering and cross-functional teams.

The Director of AI Customer Success will advise enterprise clients, ensuring successful delivery and adoption of AI solutions while driving retention and value realization. Responsibilities include customer strategy, developing success metrics, managing relationships, and collaborating with internal teams.

Lead enterprise deployment, governance, and operations for Microsoft Copilot and Power Platform across M365. Manage tenant controls, licensing/credit governance, AI risk/compliance, Microsoft vendor relationships, SharePoint/OneDrive content readiness, and analytics/reporting. Partner with architects, Security, Legal, Procurement, and business stakeholders to ensure secure, compliant, and adopted AI platform operations.

Lead design and delivery of enterprise BI for Finance: architect Power BI solutions, build data models and dashboards, develop complex SQL transformations, ensure performance and governance, align stakeholders, and mentor teammates.

Lead design and delivery of a scalable AI platform for Aladdin: build Kubernetes-based model deployment, cloud-native infrastructure, CI/CD for ML, ensure security/compliance, troubleshoot platform reliability, translate business needs into robust technical designs, and collaborate across global teams.

As a Research Product Manager, you will oversee complex research programs, turning technical ideas into execution plans and aligning research with production systems to enhance AI capabilities.

Design, build, and deploy transformer-based ML and LLM systems to automate risk investigations and decisioning. Own end-to-end pipelines (data ingestion, prompt tuning, orchestration, productionization, monitoring) and collaborate with product, engineering, and operations to deliver copilot/autopilot workflows that improve analyst productivity and eliminate manual reviews.

The Applied AI Engineer will build and maintain AI agents, manage integrations and monitor performance, ensuring quality and continuous improvement of AI tools at Zello.

Responsible for leading design projects, translating AI insights into intuitive interfaces, conducting user research, and collaborating with cross-functional teams to deliver innovative health-focused designs.

The role involves designing and operating AI systems, building data pipelines, fine-tuning models, and mentoring team members while collaborating with product and data science teams.

As Director, AI Platforms, you will lead the development of AI-enabling platform services, ensuring compliance, reliability, and adoption across teams. You will manage multi-tenant services and drive AI integration into the SDLC, shaping strategies and overseeing platform governance.

Lead enterprise AI consumption finance: define telemetry, unit-economics, allocation policies, vendor normalization, ROI and benefits realization, credit ledger governance, reporting, and cross-functional FinOps-for-AI governance with Finance, Procurement, and AI Operations.

Build a cross-platform endpoint agent to detect and attribute AI-generated code at the line level, design pipelines to capture/classify/store developer and agent activity, work with Git internals, integrate with coding agents, and ensure reliable, invisible production deployments across macOS, Linux, and Windows.

The AI Operations Lead will identify operational bottlenecks, build AI automations and workflows, and drive cross-team collaboration to enhance efficiency and establish internal AI foundations.

Own and drive AI initiatives end-to-end: plan and track milestones, manage dependencies, remove risks and blockers, coordinate vendors and resources, facilitate cross-functional decisions (Medical, Legal, Regulatory, Compliance, Privacy), run governance and reviews, and produce clear status and reporting to leadership while promoting AI-enabled operating models.