Top Artificial Intelligence Jobs

Leads Metropolis's hospitality growth strategy, commercial expansion, national account sales, partnerships, vertical marketing, and product commercialization. Owns the segment growth target and collaborates with sales, operations, marketing, product, and data teams to build market-leading hospitality solutions. Responsibilities include developing commercial structures, scaling the Recognition Platform, creating industry partnerships, translating customer insights into product-market fit, and using data-driven tools to accelerate pipeline performance and value creation.

Leads retail growth and commercial strategy, owning revenue expansion, national account wins, partnerships, B2B marketing, deal structures, product-market fit, and vertical offerings. Builds retail industry relationships, coordinates sales, product, marketing, operations, and data teams, establishes growth reporting, and represents the company through trade press, conferences, and industry thought leadership.

Leads retail growth and commercial strategy, owning segment revenue and expansion. Responsibilities include winning national accounts, developing partnerships, shaping vertical solutions and deal structures, scaling B2B marketing, collaborating with product and sales teams, building growth reporting, and representing the company through industry thought leadership. The role requires extensive retail relationships, strategic business development expertise, financial modeling, P&L management, and cross-functional leadership.

Leads hospitality-sector growth strategy, commercial expansion, national account wins, partnerships, vertical marketing, and profitable segment performance. Collaborates with sales, operations, product, marketing, and data teams to scale parking, security, recognition, and biometric technology solutions. Owns hospitality growth targets, commercial structures, product-market fit, industry positioning, dashboards, and enterprise relationships across major hospitality brands.

Leads an eLearning team developing, maintaining, and optimizing self-paced digital learning content for a clinical data platform. Owns content strategy, roadmaps, production workflows, quality standards, analytics, accessibility, and learning outcomes. Collaborates with subject matter experts, product teams, stakeholders, and external partners to translate complex concepts into effective training. Uses AI and emerging technologies to improve development and personalization, while mentoring team members and incorporating learner feedback.

Designs and implements Zero Trust architectures, leads customer engagement and solution design, gathers requirements, evaluates existing systems, and provides technical leadership for deployment optimization. The role requires deep networking and cybersecurity expertise, knowledge of NIST Zero Trust Architecture, advanced technical credentials, customer-facing communication, cloud familiarity, and the ability to apply AI tools to improve workflows and problem-solving.

Design, develop, deploy, and support foundational AI systems, including LLM inference, agentic workflows, vector search, guardrails, evaluation, orchestration, and observability. Optimize model performance, scalability, latency, throughput, hardware utilization, and cost. Establish AI governance standards, lead technical reviews, shape long-term platform strategy, and mentor senior AI engineers. Collaborate with engineering, research, product, and program teams to deliver responsible AI products.

Conduct applied AI research focused on recommendation systems and foundation models. Design, train, evaluate, validate, and implement large-scale models using PyTorch, AWS, Hugging Face, and Lightning. Collaborate with data scientists, engineers, and product managers to deliver AI products, translate research into business outcomes, and publish technical findings. Own research agendas, reproduce and extend peer-reviewed work, and optimize models for large-scale training and inference.

Design, develop, deploy, and optimize large-scale AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, and model evaluation. Lead AI architecture, orchestration, cost-performance governance, technical reviews, roadmap development, and responsible AI standards. Mentor senior technical staff and apply advanced optimization techniques to improve model scalability, latency, throughput, hardware utilization, and inference cost.

Leads the design and implementation of large-scale, cloud-native full-stack systems for cloud operations resilience. Develops distributed microservices using Python, Go, JavaScript, TypeScript, AWS, Docker, and Kubernetes. Defines platform roadmaps, architecture, engineering standards, and operational practices while improving reliability, performance, and technical debt. Mentors engineers, leads design reviews and cross-functional initiatives, evaluates emerging AI technologies, and influences enterprise technology strategy.

Build and lead development of cloud-based, full-stack systems supporting observability, connectivity, resilience, and availability. Design distributed microservices, define service boundaries, establish engineering standards, improve system performance, reduce technical debt, and implement AI-powered solutions. Collaborate with product managers and architects, influence technology strategy, mentor engineers, and drive cross-functional technical initiatives using Python, Go, JavaScript, TypeScript, AWS, Docker, and Kubernetes.

Design, develop, validate, and deploy machine learning, GenAI, LLM, and agentic solutions for enterprise healthcare operations. Build scalable Python inference APIs on Kubernetes, implement semantic search and retrieval capabilities, and maintain AI/ML pipelines. Evaluate emerging technologies, apply responsible AI practices, use AI-assisted development tools, and collaborate with technical and business stakeholders while ensuring strong documentation, coding standards, and performance monitoring.

Leads multiple software engineering teams within employee platforms, providing technical guidance, managing delivery, coaching engineers, and ensuring compliance with business requirements and service levels. Drives responsible adoption of enterprise-authorized AI-assisted development, SDLC automation, and reusable engineering practices. Oversees stakeholder relationships, project dependencies, agile delivery, security, application resiliency, and cloud-native engineering initiatives.

Own the vision, strategy, roadmap, and execution of Snapchat safety, law enforcement, and regulatory compliance products. Define goals and metrics, identify opportunities through data and user research, collaborate with engineering and cross-functional partners, translate regulatory requirements into product solutions, and drive launches. The role requires strong analytical, communication, prioritization, relationship management, and AI-focused problem-solving skills.

Manage approximately 30 enterprise agency and systems integrator partner relationships. Build strategic partnerships, advise partners on Klaviyo solutions, drive referrals, co-selling, revenue growth, co-marketing, enablement, and product adoption. Serve as a trusted consultant and product expert, present to partner audiences, develop joint business strategies, and collaborate cross-functionally with Sales, Customer Success, Marketing, Product, and Enablement. Travel may be required for partner meetings and events.

Leads Unanet’s internal data strategy and architecture for enterprise AI. Defines the shared data foundation, target architecture, governance standards, roadmap, and reusable approaches for AI assistants, agents, and workflows. Evaluates platforms and integration options, validates technical solutions, and coordinates IT, Security, Legal, Engineering, business owners, and system specialists. Advises senior leaders, establishes data quality and stewardship requirements, and helps determine when data is ready to support scalable AI initiatives.

Leads enterprise risk and resilience advisory engagements spanning cybersecurity, cloud, AI, governance, compliance, and operational readiness. Structures complex client problems, facilitates executive workshops, develops recommendations and execution plans, coordinates cross-functional experts, supports pursuits and solution development, and creates methodologies and reusable practice assets. Builds trusted executive relationships while helping grow RapidScale’s Risk & Resilience advisory practice.

Leads enterprise risk and resilience advisory engagements, structuring complex client challenges across cybersecurity, cloud, AI, governance, compliance, and transformation. Develops recommendations, roadmaps, executive presentations, proposals, scopes of work, and engagement plans. Coordinates cross-functional subject matter experts, facilitates executive workshops, supports pursuits, and contributes to methodologies, frameworks, and reusable practice-building assets.

Lead enterprise Risk & Resilience advisory engagements spanning risk, cybersecurity, cloud, AI, governance, compliance, and operational readiness. Structure ambiguous client problems, lead workstreams, facilitate executive workshops, develop recommendations and roadmaps, support proposals and solution design, coordinate subject matter experts, and create repeatable consulting methodologies and practice assets.

Leads enterprise Risk and Resilience advisory engagements across cybersecurity, cloud, AI, governance, compliance, and operational readiness. Structures complex client problems, facilitates executive workshops, develops recommendations and execution plans, supports pursuits and solution development, coordinates cross-functional experts, and creates consulting methodologies, frameworks, proposals, and reusable practice assets.

Lead enterprise risk and resilience advisory engagements from problem definition through recommendations and execution planning. Facilitate executive workshops, develop proposals and scopes of work, coordinate cybersecurity, cloud, AI, compliance, and architecture experts, and manage client communications. Translate complex business and technology risks into actionable strategies, roadmaps, and presentations. Help build repeatable consulting methodologies, frameworks, collateral, and go-to-market capabilities for RapidScale’s growing advisory practice.

Own end-to-end delivery of a multi-year autonomous manufacturing facility supporting a defense-scale shipbuilding program. Responsibilities include facility setup, robotic application sequencing, production qualification, ongoing operations coordination, NAVSEA compliance, stakeholder management, risk mitigation, milestone reporting, and maintaining program requirements and handoffs. The role requires coordinating engineering teams, external robotics partners, customer leadership, and government stakeholders while traveling to program sites up to 25% of the time.

Leads diverse technology projects and developer teams building cloud-based, full-stack risk management solutions. Provides technical direction across Agile teams, defines architecture and service integrations, mentors engineers, establishes engineering standards, and drives system performance and technical debt reduction. Develops distributed microservices and APIs using modern programming languages, databases, containers, AWS services, AI tools, CI/CD, and observability practices.

Leads enterprise workforce transformation as AI reshapes work. Owns productivity measurement, workforce planning, job architecture, role redesign, future-skills development, AI fluency, and responsible AI governance. Partners with the CPO, AI leaders, Legal, Compliance, IT, and functional executives to anticipate workforce needs, guide automation and upskilling decisions, build predictive workforce insights, and drive adoption across the organization.

Provides Six Sigma process improvement expertise across financial and healthcare operations. Supports project scoping, risk identification, resource allocation, facilitation, vendor management, strategic initiatives, data analysis, issue resolution, and project documentation. Presents findings to senior leadership and ensures projects are completed on time and within scope. The role requires project management certification, project execution experience, Six Sigma knowledge, and demonstrated artificial intelligence knowledge.