Top Artificial Intelligence Jobs

Lead forward-deployed engagements with private equity clients to build bespoke AI applications using SuperAnalyst. Scope proof-of-value, design AI use cases, drive adoption, calibrate custom skills, and translate client feedback into product roadmap improvements. Serve as the domain expert for investment workflows (research, modeling, valuation) and run demos that convert evaluations into committed deployments.

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.

Lead design of human-centered, agentic AI experiences—creating visual designs, prototypes, and scalable design systems. Collaborate with AI engineers and SMEs, use AI tools in workflow, ensure usability, trust and business impact, communicate design rationale, and mentor designers. Deliver production-ready multimodal interfaces across clients and industries. Travel may be required.

Develop, test, and maintain software applications supporting scientific research. Collaborate with engineers, scientists, and product teams to deliver cloud- and AI-enabled solutions using modern web frameworks and data platforms. Participate in Agile teams, code reviews, troubleshooting, documentation, and adoption of emerging AI tools.

Evaluate AI-generated responses (English, French, or both) using detailed annotation guidelines. Perform side-by-side comparisons, assess factuality, relevance, reasoning, tone, and cultural appropriateness for French (France). Document decisions, meet productivity and quality standards, complete training and qualification, and participate in calibration and feedback cycles.

Evaluate AI-generated responses in French and English by performing side-by-side comparisons, judging factuality, relevance, clarity, reasoning, tone, and cultural appropriateness for France. Apply detailed annotation guidelines, document rationale, meet productivity targets after qualification training, and participate in ongoing calibration and quality reviews.

Evaluate AI-generated responses in English and French (France), performing side-by-side comparisons for accuracy, relevance, reasoning, safety, tone, and usefulness. Apply detailed annotation guidelines, document decisions with concise rationale, meet productivity and quality targets, complete onboarding and qualification, and participate in ongoing calibration and feedback.

Evaluate and label AI-generated responses (English and Castilian Spanish) via side-by-side comparisons. Assess factual accuracy, relevance, completeness, reasoning, instruction-following, tone, safety, and overall usefulness using detailed annotation guidelines. Apply Castilian Spanish linguistic and cultural expertise, document decisions with concise rationale, meet productivity and quality targets, participate in training/calibration, and adapt to feedback while maintaining consistent judgment across high-volume, repetitive evaluation tasks.

Evaluate AI-generated responses in English and French (France) using detailed annotation guidelines. Perform side-by-side comparisons, assess factuality, relevance, clarity, tone, instruction-following, and cultural accuracy. Complete high-volume, time-bound tasks, document judgments, participate in training and calibration, and adapt decisions based on feedback to maintain consistent quality.

Evaluate and compare AI-generated responses in English and French (France), judging factuality, relevance, clarity, tone, instruction-following and overall usefulness. Apply detailed annotation guidelines, document decisions, meet productivity and quality targets, and participate in training, calibration, and ongoing quality reviews.

Evaluate and compare AI-generated responses (English and Castilian Spanish) using detailed guidelines. Judge accuracy, relevance, reasoning, tone, instruction-following, cultural appropriateness, and overall usefulness. Produce consistent, evidence-based annotation decisions at scale, participate in training/calibration, meet productivity and quality targets, and document rationale when required.

Lead design, development, validation, and deployment of machine learning and predictive analytics for U.S. Commercial. Integrate claims, EHR, specialty pharmacy, and commercial data to generate patient and provider insights. Partner with cross-functional teams, manage vendors, and communicate findings to leadership to inform commercial strategy and improve patient access, engagement, and treatment outcomes.

Design, build, and maintain infrastructure and processes to govern and scale enterprise AI tooling. Integrate data feeds for usage and cost metrics, support LLM lifecycle management and benchmarking, implement AI governance guardrails, collaborate with architecture and cross-functional teams, and create enablement documentation.

Lead strategy and delivery for an AI-powered claims decision-support and auto-adjudication platform. Define vision and roadmap, manage a team of product managers, partner with business, engineering, and data science, and drive adoption, impact measurement, and executive-level communication across a complex, matrixed enterprise.

Develop and productionize AI agents, RAG pipelines, and prompt-engineering frameworks using enterprise LLM platforms. Partner with business teams to translate use cases, optimize AI performance, support governance, and enable enterprise AI adoption across divisions.

Embed AI lead within Finance to identify use cases, train staff, design and deploy AI-enabled workflows integrated with ERP and finance systems, own data models and governance, ensure audit/compliance, and track measurable automation and accuracy improvements across Close, FP&A, Revenue, Audit, and Procurement.

Lead design, delivery, and scaling of production AI/ML and enterprise automation systems (LLMs, RAG, RPA) for Medicare Advantage workloads. Own data infrastructure, MLOps, integration, monitoring, compliance (HIPAA), and reliability. Mentor engineers, set engineering standards, and drive responsible AI and automation governance across the organization.

The Senior Manager will lead data modernization strategies, mentor teams, and serve as a trusted advisor to legal clients, focusing on data architecture and AI readiness.

Lead design and build of AI-driven enterprise contact center and CX solutions in pre-sales: translate workflows into prototype architectures, architect retrieval/orchestration/validation systems, run technical discovery, partner with account teams, and deliver production-grade proofs of concept that handle real-world constraints and KPIs.

Lead and deliver multiple enterprise AI and CX projects from initiation through optimization. Manage stakeholders, resources, risks, and steering committees; run workshops to define user stories and technical requirements; coordinate cross-functional services teams; track performance and report metrics; recommend product capabilities; and drive continuous improvement and customer success.

Lead development of advanced analytics and AI-driven product insights to measure and improve product ROI, cost, quality, utilization, and member outcomes. Build, test, validate, and operationalize predictive models and algorithms, prepare analytical datasets, ensure data and model quality, and partner with product and business leaders to translate results into strategic recommendations and scalable AI/ML-enabled workflows.

Lead operations and act as chief of staff for a stealth AI manufacturing planning startup: build internal systems and playbooks, manage HR/Legal/Finance vendors, run customer onboarding and multi-site rollouts, translate plant-floor feedback into product insights, own stakeholder reporting to leadership and investors, and scale processes from pilot to network deployment.

Lead and build the engineering organization for an AI-driven industrial commerce platform. Own architecture, data pipelines, ML and computer vision integrations, mobile sensor-enabled identification, enterprise system integrations (ERP/DMS), cloud infrastructure, CI/CD, and observability. Hire and mentor distributed teams, deliver rapid MVPs, and establish a scalable technical vision for identification, predictive enrichment, and commerce execution.

Own strategy and execution for a portfolio of AI-native and hyperscale customers. Serve as primary relationship owner, drive revenue, market share and product adoption, coordinate with solution architects, product marketing, OEMs and partners, forecast and train customers, and evangelize NVIDIA platforms to accelerate enterprise growth.

Lead product strategy and lifecycle for local AI system software, tools, and apps. Drive customer discovery, define requirements, coordinate cross-functional teams, set KPIs, and support go-to-market to increase adoption of local AI solutions.