Top Artificial Intelligence Jobs

Architect, build, and deploy production-grade AI/ML platforms and LLM/RAG solutions. Lead system design, CI/CD and Terraform-based IaC, ensure reliability and monitoring, mentor engineers, run incident response, and prototype emerging AI technologies.

Leads AI and automation product opportunities from business-problem discovery through MVP, pilot, adoption, and value realization. Partners with functional leaders and technical teams to define requirements, roadmaps, business cases, governance controls, user testing, and measurable outcomes. Evaluates generative AI, agents, predictive AI, automation, purchased products, and process redesign while coordinating legal, privacy, security, risk, compliance, and change-management reviews.

Designs and implements enterprise AI solution architectures addressing client business needs. Leads cloud, platform engineering, and development teams; deploys scalable AI and big-data solutions; trains and fine-tunes LLMs; advises architects and engineers; and ensures ethical, secure, compliant implementations. The role requires extensive experience with GenAI, agentic AI, Python, cloud environments, AWS AI services, and enterprise data technologies, plus a TS/SCI clearance with polygraph.

Leads Boston Scientific’s enterprise Data and AI portfolio, including strategy execution, governance, prioritization, investment evaluation, business value measurement, executive reporting, and organizational change. Partners with senior leaders to identify and scale high-impact AI initiatives, establish intake and assessment frameworks, manage resource allocation, promote responsible AI adoption, and develop a high-performing portfolio management and business transformation team.

Lead end-to-end delivery of a complex regulator-facing data and AI modernization program. Responsibilities include program governance, stakeholder engagement, budgeting, forecasting, contract performance, Agile execution, roadmap and release planning, resource management, risk mitigation, quality oversight, and executive reporting across technical and business workstreams.

Develop, train, fine-tune, evaluate, optimize, and deploy language and machine learning models, including multilingual models. Build full-stack AI applications and production pipelines using AWS platforms. Conduct model diagnostics, benchmarking, error analysis, and performance monitoring while collaborating with engineers, data scientists, and product teams. Document model workflows and technical specifications. The role requires active TS/SCI clearance with polygraph and may include occasional on-call support.

Lead enterprise customer enablement and adoption for OpenAI products, including ChatGPT Enterprise and Agents. Design and deliver onboarding, workshops, executive briefings, hackathons, and training programs for business and technical audiences. Drive activation, sustained usage, and measurable business value throughout the customer lifecycle. Develop reusable playbooks, synthesize customer feedback, support product improvements, and partner with Sales, Solution Architects, and Delivery Leads. Fluent business-level Korean is required for engaging Korean-speaking customers.

Lead enterprise customer enablement and adoption of OpenAI products, including ChatGPT Enterprise and Agents. Design and deliver onboarding, workshops, executive briefings, hackathons, and advanced training for business and technical audiences. Drive activation, sustained usage, and measurable business value across the customer lifecycle. Develop reusable training assets and playbooks, serve as a product subject matter expert, synthesize customer feedback, and partner with Sales, Solution Architects, and Delivery Leads to improve adoption.

Owns post-sales enablement and adoption of OpenAI products across enterprise customers. Designs and delivers onboarding, workshops, trainings, executive briefings, and hackathons for business and technical audiences. Drives activation, sustained usage, expansion, and measurable business value while developing reusable playbooks and training assets. Serves as a product subject matter expert, gathers customer feedback, identifies scalable adoption patterns, and partners with Sales, Solution Architects, and Delivery Leads.

Serve as the first sales engineer for an AI software company focused on financial services. Own technical discovery, product demonstrations, solution architecture, and security reviews with banks, asset managers, and insurers. Partner with founders throughout the sales cycle, support technical buyers and executives, and build the company’s sales engineering function.

Own product strategy and major initiatives as Ploy’s first product manager. Partner with founders, engineering, design, and go-to-market teams to improve activation, marketing workflows, AI agent experiences, pricing, packaging, and upgrades. Use customer feedback and product data to prioritize, ship, and iterate on impactful products while managing cross-functional execution.

Build backend and developer productivity systems that help engineers and AI agents ship software safely at high volume. Responsibilities include rebuilding CI/CD, creating ephemeral development environments, automating testing and deployments, developing AI code review and security pipelines, conducting continuous penetration testing, securing agent access, and measuring improvements to the development lifecycle. The role also contributes to product features across video creation, rendering, and developer platforms.

Leads Healogics’ enterprise data and AI strategy, architecture, operating model, roadmap, and investment priorities. Oversees data engineering, analytics, applied AI, and solution development teams while setting technical standards and reviewing complex architectures. Guides enterprise reporting, Databricks strategy, generative AI initiatives, governance, security, and responsible AI. Partners with executives to prioritize high-value initiatives, manages budgets and vendors, develops technical leaders, and ensures scalable, supportable solutions deliver measurable clinical and business outcomes.

Leads enterprise-wide clinician experience and nursing innovation strategy across a national clinical workforce. Analyzes engagement, turnover, and workforce data; develops retention and economic mobility programs; standardizes clinical roles; and scales recognition and engagement initiatives. Partners with executive, clinical, operations, people, and IT leaders to optimize workflows, evaluate AI and digital solutions, drive change management, and ensure frontline clinician feedback shapes policies, tools, and training.

Develop software and algorithms for autonomous agricultural and construction equipment. Responsibilities include sensor fusion, mapping, localization, object tracking, perception, vehicle planning, machine learning, data modeling, and complex software architectures. The role collaborates with agile engineering teams and requires expertise in autonomy, AI, machine learning, and software development using C++, Python, and MATLAB. Occasional travel and onsite work are expected.

Supports and improves enterprise AI platforms and infrastructure across cloud and on-premises environments. Builds automation and self-service tooling, troubleshoots LLM integrations and production systems, monitors AI usage and performance, and maintains deployment and observability workflows. Collaborates with engineering, product, business systems, and AI strategy teams to improve reliability, usability, and operational efficiency of AI solutions.

Support and scale cloud, DevOps, and production ML infrastructure. Responsibilities include managing AWS, Databricks, SageMaker, Kubernetes, CI/CD pipelines, Infrastructure as Code, model serving, monitoring, security, observability, incident response, and disaster recovery. The role automates deployments and operational processes, improves reliability, supports AI and agentic products, and collaborates with software, ML, QA, security, and support teams.

Leads machine learning research strategy, advanced algorithm development, large-scale research programs, and cross-functional industry collaborations. Mentors research teams, drives innovation, optimizes research processes, and contributes to the broader machine learning community through publications, presentations, and industry engagement. Applies machine learning research to real-world challenges and shapes long-term organizational research initiatives.

Leads DISCO’s machine learning research strategy, directs advanced algorithm and methodology development, oversees large-scale research programs, and manages research teams. Collaborates with industry partners and cross-functional stakeholders to apply machine learning to real-world challenges. Develops long-term research plans, mentors researchers, optimizes research processes, and contributes to the broader research community through publications, presentations, and industry engagement.

Manage federal government programs and contracts within National Security Operations. Responsibilities include developing program policies, leading project teams, monitoring progress and risks, implementing mitigation strategies, coordinating customers and internal stakeholders, preparing reports, leading program reviews, and improving processes. Requires extensive federal program management and government contracting experience, direct customer engagement, knowledge of FAR/DFAR regulations, and an active TS/SCI clearance with polygraph.

Lead full-cycle recruiting for Anthropic’s Applied AI team, focusing on Solutions Architects, Pre-Sales Engineers, managers, and other customer-facing technical roles. Develop sourcing and hiring strategies, build pipelines involving LLMs and cloud architecture, partner with technical leaders, deliver personalized candidate experiences, and provide market insights on compensation and talent availability. The role also involves using AI tools to improve recruiting efficiency and collaborating across the GTM recruiting organization.

Build foundational enterprise agentic AI platform capabilities, including agent runtimes, control planes, governance, security, discovery, observability, evaluation, developer tooling, and AI-specific CI/CD. Design scalable distributed services, APIs, integrations, SDKs, and automation supporting agent deployment across multiple models and platforms. Establish secure, reliable, explainable, and cost-efficient production patterns while partnering with product, infrastructure, security, risk, and governance teams.

Build and operate production-grade agentic AI systems, including LLM-powered customer features, financial workflow automation, RAG pipelines, orchestration infrastructure, and evaluation tooling. Own reliability, latency, cost, safety, and auditability in a regulated financial environment. Partner with product and design teams to deliver customer-focused solutions and lead technical execution across backend systems, APIs, data pipelines, cloud infrastructure, and applied AI.

Develop web-based interfaces and software for embedded products, integrating REST APIs, WebSockets, networking, and AI agents. Collaborate with firmware, hardware, UX, testing, and product teams to deliver integrated solutions. Troubleshoot issues across interfaces, backend services, network communication, and embedded-device layers while contributing to design, testing, code reviews, documentation, and workflow automation.

Owns the post-sale client success organization across operations and account management. This executive will build scalable onboarding, delivery, QA, service-level, reporting, and automation systems; drive retention, renewal, expansion, and revenue outcomes; unify client experiences across multiple product lines; develop senior leaders; apply AI to client-facing workflows; and represent client needs on the leadership team.