Top Artificial Intelligence Jobs

This role involves developing AI/ML architectures, resolving complex issues, and partnering with stakeholders to enhance business outcomes through technology and data.

Embeds with commercial teams to identify growth and margin opportunities, then designs, builds, deploys, and maintains production AI agents, LLM pipelines, data products, and internal tools. Owns architecture, evaluation, reliability, observability, cost, adoption, and measurable business outcomes. Partners with senior leaders, finance teams, engineers, and operators to translate technical solutions into commercial impact and develop repeatable AI capabilities.

Own and build production AI agents and automations across Finance, including FP&A, Accounting, Audit, Tax, and Treasury. Lead the AI roadmap, quantify business outcomes, establish governance and SOX controls, integrate systems such as Oracle ERP and EPM, and manage a technical finance team. Partner with executives, technology, data, and audit stakeholders to scale secure, auditable automation that improves margin, productivity, and enterprise value.

Own technical relationships with strategic enterprise customers throughout Moveworks implementations. Design AI agent solutions, enterprise integrations, workflows, and automations using APIs, iPaaS tools, cloud functions, and scripting. Advise customers on agentic AI roadmaps, coordinate cross-functional delivery, develop reusable capabilities, and mentor engineers. The role combines solution architecture, hands-on implementation, technical consulting, executive communication, and up to 25% travel.

Leads architecture strategy, roadmaps, governance, and solution design for a regulated enterprise’s digital experience portfolio. Partners with business, product, marketing, design, data, security, and engineering teams to deliver secure, scalable, reusable web and mobile experiences. Oversees modernization, cloud and SaaS adoption, integration patterns, technology risk, and Agile/DevOps delivery. Defines architectural approaches for AI-enabled channels, conversational experiences, personalization, automation, and reusable digital platform services.

Serve as a technical partner to sales and customer success teams, advising high-value customers on cloud infrastructure and AI/ML solutions. Responsibilities include architecture reviews, proofs of concept, demos, onboarding, technical workshops, infrastructure optimization, LLM deployment and fine-tuning, GPU workload optimization, AI application design, data pipeline and database integration, escalations, documentation, and development of tools for premium customers. Collaborate globally with Engineering, Product, Support, and account teams.

Design, build, and operate production AI automations and agentic workflows for Toast’s customer care systems. Integrate LLMs with Salesforce Service Cloud, Amazon Connect, and workflow platforms; develop autonomous actions with human oversight; test, monitor, and improve system reliability, accuracy, latency, and cost. Collaborate with software engineers, Salesforce developers, and care operations stakeholders to translate workflows into scalable intelligent solutions.

Own the vision, roadmap, and delivery of AI use-case products, including LLM systems, agents, and evaluation pipelines. Translate customer and business needs into technical product requirements, make build or buy decisions, define AI quality and business metrics, and guide launches through governance and regulatory review. Lead cross-functional teams, manage executive stakeholders, establish AI product standards, mentor product managers, and ensure product quality, safety, adoption, and impact.

Build and support foundational AI platform components, including LLM inference, model training, similarity search, guardrails, evaluation, governance, experimentation, and observability. Optimize large-scale AI systems for scalability, latency, throughput, hardware utilization, and cost. Contribute to technical strategy and roadmap, collaborate cross-functionally, and lead or mentor engineering teams while applying emerging AI research in production.

Owns AI opportunity intake, qualification, routing, and assignment operations. Manages CRM configuration, dashboards, KPI reporting, SLA tracking, data hygiene, audits, and lead-flow process improvements. Partners with business consultants, technical teams, revenue operations, and practice leaders to develop agentic workflow automation with human oversight. Routes qualified opportunities, resolves stalled or escalated leads, documents requirements, and uses performance data to improve routing accuracy, speed, and pipeline visibility.

Owns AI opportunity intake, qualification, routing, assignment, CRM workflows, pipeline reporting, and process improvement. The role manages lead-flow controls, SLAs, dashboards, KPI tracking, human-in-the-loop routing, agentic automation requirements, and cross-functional coordination across sales and AI practice teams.

Build AI applications, agents, integrations, and automated workflows that transform technical information into customer documentation. Partner with the Documentation team to use LLMs, agentic AI, and automation to improve content creation, maintenance, publishing, and delivery. Reduce manual effort, increase access to technical knowledge, and identify additional customer-facing workflows where AI can improve efficiency and experience.

Support firm-wide AI and digital transformation initiatives by conducting journey assessments, data-driven analyses, financial modeling, competitor research, and executive-ready presentations. Partner with cross-functional teams to define future-state improvements, size impact, develop business cases, and coordinate implementation and operating model planning.

Own product marketing for Braze Decisioning Studio, including positioning, messaging, launches, competitive strategy, pricing and packaging input, field enablement, and portfolio narrative. Translate complex AI and data technologies for technical and business audiences, influence product roadmaps, engage customers and analysts, and measure impact through pipeline, adoption, expansion, and competitive win rates. This senior individual contributor role requires cross-functional execution, technical credibility, strong writing, and enterprise AI and martech expertise.

Own product marketing for Braze Decisioning Studio, including positioning, messaging, launches, competitive strategy, pricing and packaging input, field enablement, customer insights, and portfolio narrative. The role translates complex AI and data infrastructure concepts for technical and business audiences, influences product roadmaps, partners across Product, Engineering, Sales, and Marketing, and measures success through pipeline, adoption, expansion, and competitive win rates.

Own product marketing for Braze Decisioning Studio, including positioning, messaging, launches, competitive strategy, pricing and packaging input, field enablement, and portfolio narrative. Translate complex AI and data technologies for technical and business audiences, influence product roadmaps, engage customers and analysts, develop thought leadership, and measure impact through pipeline, adoption, expansion, and competitive win rates.

Build and scale AI platform infrastructure for internal agents across AWS/GCP. Integrate identity (Okta, OAuth2/OIDC), implement agentic security, containerized deployments (Docker/Kubernetes), CI/CD and Terraform-based pipelines, run vendor evaluations, and design observability/telemetry for LLM-driven workflows while collaborating with security, identity, and engineering teams.

Architect and build reliable, scalable AI platform services supporting model training and inference across hybrid-cloud environments. Develop reusable APIs, SDKs, tooling, and reference architectures; establish observability, resilience, security, automation, and cost-optimization standards. Partner with engineering and product teams to deliver platform capabilities, meet reliability targets, resolve production incidents, and drive remediation. Mentor engineers and promote responsible, secure use of AI-assisted development tools.

Leads architecture and hands-on development of scalable ML and generative AI platforms. Builds Python APIs and SDKs, Databricks data and ML workflows, agentic AI capabilities, model integrations, infrastructure automation, and CI/CD pipelines. Ensures reliability, monitoring, security, performance, and cost efficiency while mentoring engineers, partnering with data science and product teams, and establishing AI-assisted engineering quality standards.

Leads AI/ML initiatives by defining solution roadmaps, developing and deploying machine learning, deep learning, NLP, and generative AI models, and building batch and real-time production pipelines. Partners with product, engineering, business, legal, and compliance teams to identify impactful use cases, operationalize models on AWS, evaluate performance, and communicate results to technical and executive stakeholders.

Develop systems software, profiling tools, benchmarks, and experimentation frameworks for LLM training, inference, and agentic AI workloads. Optimize performance across GPUs, CPUs, memory, storage, and distributed systems, including caching, scheduling, data placement, and state management. Analyze experimental results and collaborate with research and engineering teams on AI infrastructure innovations, technical publications, intellectual property, and future platform designs.

Own the architecture and technical direction of Square’s go-to-market technology stack. Design, build, and operate production AI agents and automated workflows that improve sales productivity. Lead complex initiatives through architecture, implementation, testing, deployment, and operations; establish AI evaluation, observability, security, reliability, and human-oversight practices. Partner with Sales, Product, Data, and Engineering teams to translate business needs into scalable solutions, guide integrations and build-versus-buy decisions, and mentor engineers through influence and technical leadership.

Own the architecture and technical strategy for Square’s go-to-market systems. Build and operate production AI agents, automated workflows, and integrations that improve sales productivity. Lead complex initiatives through architecture, implementation, testing, deployment, and operations while establishing AI evaluation, observability, security, reliability, and human-oversight practices. Partner with Sales, Product, Data, and Engineering leaders to translate business needs into scalable solutions, make build-versus-buy decisions, mentor engineers, and improve business impact through data and user feedback.

Lead product marketing for an AI-powered video security platform. Own market strategy, positioning, messaging, go-to-market planning, product launches, sales and channel enablement, customer insights, and thought leadership. Partner cross-functionally with Product, Engineering, Sales, Marketing, and Customer Success to translate technical capabilities into compelling customer value, influence roadmap priorities, and drive measurable business outcomes in a high-growth startup environment.

Develop and implement generative AI solutions for client engagements, including contact center applications, machine learning and NLP integrations, prompt engineering, LLM evaluation, and LLMOps governance. Use Python, Azure AI Services, Google Vertex AI, LangChain, and LLM APIs to build, deploy, monitor, and refine AI applications while supporting data analytics and client outcomes.