Top Artificial Intelligence Jobs

Lead strategy and commercial relationships for HealthVeritys AI ecosystem. Drive go-to-market planning, identify and close enterprise data licensing and channel partnerships, present solutions and lead technical due diligence, manage opportunities from proposal to contract, and coordinate cross-functional teams while establishing team goals and operational excellence.

Lead research and thought leadership in marketing measurement and AI-enabled decisioning. Produce actionable insights, client-facing advisory, presentations, and peer-reviewed content. Mentor analysts, support sales and GTM, improve research processes, and drive adoption of marketing analytics methods (MMM, experimentation, attribution, forecasting) and AI-powered measurement across clients and teams.

Define and govern enterprise AI architecture, standards, and reference implementations. Enable GenAI/ML platforms, integrations, and responsible AI guardrails. Partner with engineering, data science, cybersecurity, and business teams to translate use cases into scalable, secure production designs and drive adoption across the enterprise.

Lead design, deployment, and management of AIOps solutions using Splunk to provide predictive analytics and automated closed-loop incident response. Integrate telemetry from SolarWinds, ServiceNow, and other sources, build ML models with Splunk MLTK, ensure compliance with DoW security protocols, and coordinate with cyber defense teams.

Lead content strategy and AI-enabled content transformation for Consumer line of business. Define AI-driven content frameworks, partner across digital, SEO, analytics and product teams, modernize content planning/creation/measurement, and operationalize scalable playbooks to improve engagement and business outcomes while managing stakeholders and budgets in a matrixed, regulated environment.

Transform AI prototypes into secure, scalable production systems by re-architecting code, designing cloud infrastructure (AWS/Azure), implementing CI/CD, containerizing (Docker/Kubernetes), ensuring security/compliance, building APIs, monitoring, and enabling developer productivity with infrastructure-as-code, reusable templates, and documentation.

Work directly with customers to define AI strategy, identify high-impact use cases, and design, build, and ship production-grade AI agents and workflows. Rapidly deploy solutions in real environments, iterate with users and data, and contribute learnings back to the company's Mosaic product.

Lead program management for AI Transformation and Design Foundations, building roadmaps, governance, operating models, adoption plans, and metrics. Coordinate cross-functional teams (design, engineering, research, security, AI) to operationalize AI-assisted design practices, remove blockers, track risks and impact, and create playbooks and communication for scalable adoption.

Design, develop, and deploy production-grade generative AI and agentic systems (LLMs, RAG, AI agents). Build document intelligence, retrieval pipelines, vector search, and monitoring frameworks. Collaborate with risk, compliance, product, and engineering to deliver scalable, governed GenAI solutions in regulated environments.

Design, build, and maintain scalable, secure data pipelines and platforms to acquire, transform, and store large financial datasets. Enable AI/GenAI-ready data foundations for model training, inference, retrieval, and RAG workflows. Collaborate with cross-functional teams, ensure data quality, governance, observability, and compliance, and support production deployments and troubleshooting.

Lead AI technical strategy and roadmap across product portfolio. Drive design, development, and production deployment of large-scale ML and generative AI models (including LLMs), mentor teams, align stakeholders, mitigate risks, and ensure timely delivery of AI capabilities.

Develop, deploy, and own RTL-to-GDSII physical design methodology and CAD flows for IP delivery. Automate PPA exploration, document flows, partner with design teams and EDA vendors, qualify new nodes/PDKs and EDA releases, and apply ML/LLMs where they improve flow optimization and scalability.

Hands-on technical lead for a small team building AI-native, agentic automation systems. Code daily (Python/Flask, React) and design LLM-driven autonomous agents, ETL/data pipelines, MySQL schemas, and integrations. Own delivery, CI/CD discipline, code reviews, and enforce development standards while mentoring distributed team and ensuring compliance and governance.

Design and validate high-bandwidth interconnects for AI clusters across copper and optical media. Define architectures, perform link and channel budget analysis, lead qualification and reliability testing, develop validation plans for transceivers and cables up to 1.6T, and coordinate with suppliers and manufacturing.

Lead the creation and execution of AIUC's content strategy to establish AIUC-1 and founders as the leading voices on enterprise AI trust. Build distinct content brands, run content experiments to drive leads, create a research/publishing program, own website narrative, produce technical and thought-leadership content, and scale a small content team or agency relationships.

Work directly with founders on high-priority, cross-functional projects: talent brand strategy, consortium onboarding, partner relationships, and co-marketing. High-impact generalist role with mentorship and opportunities to rotate into specialized functions.

Lead generative AI image production for realistic personas and models. Build and optimize scalable generative pipelines, automate batch workflows, evaluate new models/tools, define technical direction and best practices, and improve image quality, consistency, speed, and cost-efficiency.

Manage and optimize AI-enhanced compliance and records systems for safety, HR, and operations. Build filing standards, track training/certifications/equipment, support prequalification platforms, prepare audits, maintain dashboards and reports, and coordinate cross-functionally to ensure audit-ready documentation and automated compliance follow-up.

Lead partner-facing product strategy for NIQ's AI Commerce partnerships: translate partner technical and commercial needs (MCP, API) into product requirements, drive roadmap and financial outcomes, lead cross-functional teams, influence executives, and represent partnership direction externally.

Design, build, deploy, and maintain AI agents, copilots, and LLM-based solutions (RAG, prompt engineering). Build APIs, integrations, and microservices, prepare data, monitor and optimize models, ensure governance/security, and partner with stakeholders to deliver production-ready AI that drives business impact.

Design and implement software solutions with cross-functional teams; produce technical specifications and documentation; write, test, deploy code; perform code reviews; provide technical support; collaborate on QA/testing; stay current with tech trends and recommend integrations.

Design and implement AI-enabled workflow orchestration, integrations, and automation pipelines across legal workflows. Build agent orchestration, vector retrieval, API/webhook integrations, monitor reliability and performance, ensure governance and compliance, and collaborate with product, legal, and operations teams to scale AI-native legal service delivery.

Design and implement AI-native workflow orchestration and automation systems for legal service delivery. Build integrations between AI platforms, CRMs, document systems, client portals, and payment systems; implement retrieval, prompt orchestration, event-driven pipelines, and observability. Monitor reliability, troubleshoot bottlenecks, support compliance and governance, and document architectures while evaluating emerging automation tools.

Design, build, and maintain AI-enabled workflow orchestration and automation systems integrating AI models, CRMs, document systems, client portals, and internal tools; implement API/webhook integrations, vector retrieval, prompt orchestration, monitor reliability/performance, and ensure governance, compliance, and scalability.

Design, build, and maintain AI-enabled workflow orchestration and automation systems for legal service delivery. Implement integrations between AI platforms, CRMs, document systems, client portals, and payment systems. Develop event-driven pipelines, retrieval and prompt orchestration, agent workflows, and observability. Monitor reliability, troubleshoot integrations, support compliance and governance, and document architectures and operational standards.