Top Artificial Intelligence Jobs

The AI Marketer/DevRel will enhance brand awareness through technical content, community engagement, and storytelling while fostering developer relations.

Own full enterprise sales cycles for a SaaS AI platform: run tailored demos, manage 2-week trials, engage multi-stakeholder buyers across R&D, regulatory, legal and procurement, partner with a solutions engineer, and help refine the sales playbook while closing complex deals at large manufacturers.

Lead design and implementation of AI and data governance frameworks, privacy guardrails, metadata standards, and compliance with GDPR/HIPAA/CCPA/NIST AI RMF. Monitor and audit models for bias, explainability, and transparency; partner with engineers, stewards, and leaders to embed ethical decision-making, set KPIs, run audits, and produce dashboards and reports to drive governance adoption.

Lead the architecture, build, and deployment of AI-driven automation and intelligent systems to solve security, compliance, and risk challenges. Develop real-time intelligence, workflow automation, and risk-based decision-making tools, and engage customers and partners to refine and deploy production-grade solutions.

Coordinate AI research, training-data, and data operations programs. Serve as the day-to-day contact between leadership, research teams, and domain experts; track deliverables, onboard experts, document processes, monitor quality, and drive project communications using Excel/Google Sheets and SQL.

The Senior Product Manager will prioritize and deliver AI products, support cross-functional teams, enhance key metrics, and drive market leadership through innovation and research.

The Staff AI Engineer will analyze AI quality, implement improvements, manage projects, collaborate with teams, and shape AI capabilities in a remote-first environment.

Build and deploy autonomous AI agents and GenAI solutions at scale. Design and operationalize distributed data flows, agent orchestration, memory/RAG systems, and integrations with LLM APIs. Collaborate globally, prototype state-of-the-art ML/GenAI technologies, and ensure scalable, reliable cloud-native architectures.

Lead executive communications for the AI Monetization team: craft messaging, develop collateral, advise and coach executives, manage internal/external visibility, handle urgent communications and reputation risk, and apply AI tools to support targeted messaging.

Lead AI transformation engagements using Copilot Studio, Dynamics 365, Power Platform, Dataverse and Azure. Run discovery and design workshops, create scalable secure architectures, rapid prototypes, and align technical solutions with business value while collaborating with sales and stakeholders.

Drive qualification and pipeline growth for cloud, data, and AI solutions in Education. Lead discovery, build business cases, run workshops and demos, coordinate partners, and close deals to accelerate cloud and AI adoption while maintaining pipeline hygiene and customer skilling.

Build and ship AI-native workflows and prototypes for finance/accounting use cases, process large unstructured datasets, iterate with customer feedback, and design analytics-driven evaluation systems to improve product stability and value.

Design, build, and ship technical growth mechanisms (acquisition funnels, onboarding, referrals, activation, monetization). Own acquisition budgets, tracking specs, analytics, and experiments. Rapidly prototype AI-driven growth hypotheses, present business cases and roadmaps, and translate experiment data into clear recommendations to secure executive and partner buy-in.

Operate and improve large-scale HPC GPU clusters for AI model training and inference. Build observability, automation, CI/CD, and incident response tooling; lead on-call rotations, ensure security/compliance, collaborate with ML engineers, and optimize capacity and costs for production ML workloads.

Design, train, and evaluate Responsible AI components: fine-tune LLMs (including RLHF), build adversarial agent evaluations and safety mitigations, collaborate with engineering to deploy mitigations at scale, monitor operational performance, and troubleshoot end-to-end issues.

Lead AI risk assessments, reviews, and monitoring to support AI governance at a financial institution. Evaluate internal and third-party AI solutions, maintain an enterprise AI inventory, analyze controls and risk metrics, build dashboards and reports, and provide quantitative and advisory support across stakeholders to enable responsible AI adoption and regulatory readiness.

Lead marketing AI deployment and measurement: identify and prioritize AI opportunities, manage cross-functional rollouts, build attribution and KPI reporting in Power BI, improve data architecture and quality, run journey and lead-scoring analyses, and shape GTM tools and processes to optimize pipeline and revenue.

Own and operate the realtime voice stack and call-data platform end-to-end: telephony/WebRTC integration, streaming STT/TTS, realtime voice agents, call-to-transcript pipelines, data warehousing, analytics, and dashboards. Build AI-native workflows, RAG/search, human-in-the-loop flows, and optimize performance, latency, and cost. Mentor teammates and collaborate across product and subject-matter experts.

Build and maintain full-stack product and AI systems: React/React Native frontends, Node.js services, LLM-powered features (agents, RAG), integrations, monitoring, and scalable automation. Ship production features, ensure reliability, and mentor teammates.

The Senior Staff Engineer will lead the development of an underwriting platform, enhance AI integration, mentor junior engineers, and collaborate with teams to transform GEICO's underwriting processes through tech innovations.

Design, build, and maintain production-grade conversational AI platform features and backend services. Deliver event-driven integrations, ensure reliability and security, optimize databases, support production incidents, improve observability, and mentor engineers while collaborating with product, QA, and design.

Designs, builds, and supports Power Platform and AI solutions (Power Apps, Power Pages, Power Automate, Copilot) and Power BI reports. Connects and transforms data from CRM/ERP/PSA systems, implements security and governance, troubleshoots performance and refresh issues, and supports testing, training, and documentation for client and managed-service engagements.

Design, build, and sustain AI analytics stack components including web frontends, FastAPI services, containerized deployments, and data layers. Integrate LLM capabilities (prompting, tool-calling, RAG), establish CI/CD pipelines, work with PostgreSQL/MySQL, and collaborate cross-functionally to deliver secure, maintainable AI-enabled software solutions.

Design and implement an MLIR-based AI compiler for GPU inference: develop graph representations and dialects, optimize performance and memory, define APIs, generate kernels, and collaborate with framework and hardware teams to enable new model patterns and GPU features.

Lead strategic engagement with AI platform and tools ecosystem, enhance partner product direction, technical onboarding, and ecosystem growth with NVIDIA's technology.