Top Artificial Intelligence Jobs

Designs, implements, operates, and improves shared university AI services. Consults with academic and administrative units, evaluates AI platforms and vendors, prototypes integrations, and moves pilots into sustainable enterprise solutions. The role develops governance guardrails, service processes, business cases, documentation, and adoption metrics while coordinating with security, legal, procurement, architecture, and data governance teams. It also supports AI communities of practice and communicates technical capabilities, limitations, risks, and recommendations to technical and non-technical stakeholders.

Architect and develop bare-metal C firmware for RISC-V management cores controlling AI/HPC networking acceleration engines. Responsibilities include secure firmware loading, image authentication, boot and reset sequencing, health validation, multi-die firmware distribution, updates, hardware/software interface definition, simulator-based testing, architecture standards, code reviews, and technical mentorship.

Lead the AI Platform team in building reliable, secure, observable infrastructure, shared services, deployment patterns, and operational practices for AI capabilities. Set technical priorities, coordinate cross-team dependencies, guide architecture and production operations, improve developer experience, and coach engineers while contributing to complex technical work.

Leads research, development, productionization, and deployment of advanced AI models powering context-engine and agentic platforms. Builds multimodal ingestion, entity-resolution, knowledge-graph, and agentic-search capabilities; designs experiments; collaborates with product and infrastructure teams; mentors engineers; contributes to research and technical documentation; and supports customer-focused product delivery.

Lead software architecture for robotics and AI systems using C++ and Python. Design real-time robotics control, planning, optimization, generative AI, operator GUIs, diagnostics, simulation, and production integrations. Establish scalable infrastructure, CI/CD, containerization, testing, and deployment practices. Integrate robotics stacks, hardware, sensors, and manufacturing systems while leading technical reviews, mentoring engineers, commissioning systems, and troubleshooting production hardware.

AI Engineering intern developing agentic AI workflows and internal tools that combine LLMs, APIs, and automation frameworks. Responsibilities include prototyping agent architectures, evaluating reliability and failure modes, documenting experiments, and presenting solutions to customers and leadership. The 10–12 week hybrid program requires Python and SQL experience, API and JSON familiarity, foundational LLM knowledge, and enrollment in a technical degree program with graduation in 2027 or 2028.

Design, prototype, and develop agentic AI workflows and internal tools using LLMs, APIs, and automation frameworks. Experiment with agent architectures, evaluate reliability and failure modes, document designs, and present solutions to customers and leadership. The 10–12 week hybrid summer program includes mentorship from senior engineers and architects in a fintech environment.

Leads global financial analysis and portfolio management for public cloud and artificial intelligence infrastructure rate optimization. Responsibilities include evaluating compute, database, and GPU commitments; developing financial models, forecasts, scenarios, and business cases; tracking utilization and savings; analyzing month-end results; managing implementation changes; and preparing executive-ready reporting and presentations. Partners across finance, technology, controllership, and strategic sourcing to improve efficiency, governance, and infrastructure spending outcomes.

Lead product strategy and roadmap for AI-driven content experiences across Edge, Windows, Copilot and partner surfaces. Build scalable trust-and-safety systems, define policies for compliance and risk, partner with policy, engineering, data science, legal and operations, and drive cross-functional execution and metrics to reduce harm and maintain content quality at scale.

Own the strategy, roadmap, and execution of Docker’s AI Gateway, enabling secure model access for developer and enterprise AI agent workflows. Responsibilities include simplifying onboarding, shaping APIs and integrations, defining governance and access controls, managing model interoperability, optimizing routing and inference costs, and driving launches. The role partners with engineering, design, customers, security stakeholders, and inference providers.

Execute technical go-to-market strategy for Okta’s AI identity products. Maintain the Blueprint Maturity Model, implementation guides, templates, demos, and technical collateral; track product releases, roadmap changes, competitors, and protocol developments; gather field feedback; and support sales enablement, customer sessions, and technical events. The role requires hands-on work with SaaS consoles, CLIs, APIs, identity protocols, technical writing, and cross-functional collaboration, with occasional customer travel.

Design, build, and own a multi-tenant enterprise SaaS backend that feeds ML data and BI. Collaborate with product, data science, UX, and users to deliver scalable, reliable customer-facing AI solutions. Drive systems design, database schemas, development lifecycle standards, technical docs, and code reviews while using AI/agentic tools to accelerate development.

Drives SEO and AI visibility for higher education clients by conducting audits, keyword and prompt research, analyzing performance data, and recommending improvements to crawlability, indexation, structured data, content, and discoverability. The role advises partners, presents insights, develops SEO and GEO strategies, monitors emerging search trends, and uses analytics and optimization tools to improve organic search and AI-driven discovery.

Build shared APIs, SDKs, evaluation infrastructure, tracing, observability, and model-routing systems for Suno’s AI agent platform. Support engineering teams adopting the platform, improve reliability and scalability with Infrastructure, and manage provider fallbacks, rate limits, and cost controls. The role requires production backend or platform experience, distributed systems expertise, and experience supporting developer teams and deploying LLM or agent systems.

Build and operate backend systems for Suno’s multi-step AI music agent. Design evaluation datasets, graders, regression sets, release gates, and data pipelines for nondeterministic systems. Create internal tools for reviewing model output, support production launches and on-call operations, and collaborate with ML engineers, product managers, and partner teams. The role also involves mentoring engineers and shipping high-traffic creative music features.

Leads the enterprise strategy and roadmap for Commercial AI, digital products, Salesforce, marketing technology, customer intelligence, data, analytics, and agentic capabilities. Partners with senior business and technology leaders to prioritize investments, shape architecture, scale AI-enabled commercial experiences, manage strategic technology partnerships, and build a high-performing product organization. Drives measurable outcomes across sales productivity, customer engagement, opportunity identification, revenue enablement, and value realization.

Leads enterprise Data and AI platform governance, operations, adoption, optimization, security, and compliance. Manages analytics strategy and team performance while overseeing data pipelines, predictive models, analytical databases, and workflows. Partners with technical and business stakeholders to translate needs into solutions, improve platform value, establish standards, and support responsible innovation. Responsibilities include recruiting, coaching, mentoring, cost optimization, vendor management, and communicating complex technical findings to diverse audiences.

Leads Zuora’s AI platform strategy, architecture, and development. Builds secure, scalable shared capabilities for AI-powered products, agentic workflows, model orchestration, retrieval, context management, and enterprise system integration. Establishes governance, evaluation, observability, reliability, cost controls, and authorization standards while translating platform investments into business outcomes. Partners across Product, Engineering, Data, Security, Legal, and Compliance, and builds a high-impact AI platform organization.

Leads development of agentic AI capabilities that execute multi-step workflows across desktop engineering tools. Owns agent architecture, evaluation frameworks, benchmarking, cost efficiency, user-story validation, and production delivery. Serves as player-coach for a small AI engineering team, writing code, reviewing designs, and setting technical direction. Requires expertise in LLM application architecture, real-world agents, Python, desktop automation, engineering software domains, and enterprise deployment constraints.

Leads the company’s AI governance program by developing frameworks, policies, controls, inventories, approval processes, and monitoring for AI and LLM tools. Partners with security, engineering, IT operations, risk, legal, and compliance teams to manage AI risks, third-party due diligence, data protection, regulatory compliance, audits, training, and responsible AI adoption. Tracks emerging regulations and standards while measuring program effectiveness and driving continuous improvement.

Own regional P&L, ROI, revenue, unit sales, gross margin, team structure, hiring, and resource allocation for Western Pennsylvania. Prioritize market verticals, lead regional sales execution, manage KAM and partner routing, establish performance targets, report pipeline and hiring progress to senior leadership, and develop investment cases for regional expansion. The role requires extensive travel and leadership of direct and channel B2B sales across multiple verticals.

Build and scale production AI innovations, including agentic systems, real-time voice, and multimodal experiences. Research models and frameworks, prototype rapidly, run safe experiments, and measure quality, latency, cost, and impact. Extend agent-platform orchestration, tool use, and evaluation capabilities. Make cross-team technical decisions, establish engineering practices, mentor others, communicate with technical and executive audiences, and partner with product, design, and engineering to turn validated concepts into secure, reliable platform products.

Build and deploy data integrations, AI-powered workflows, and internal tools. Responsibilities include connecting APIs and databases, improving data quality, implementing validation and monitoring, developing retrieval and automation applications, translating business needs into deliverables, deploying production solutions, documenting systems, and transferring knowledge to internal teams.

Own the conversational intelligence layer of a consumer application, including agent architecture, prompt design, tool calling, reasoning, memory, error handling, response rendering, model routing, and evaluation. Build dependable multi-turn language-model experiences, improve search and ranking quality, and launch personalized AI features for live users. The role requires broad applied AI expertise, strong analytical ability, and experience diagnosing production issues.

Leads Microsoft’s AI Workforce sales business across state and local government, education, academic medical centers, and software customers. Owns strategy, revenue growth, pipeline, forecasting, competitive execution, and customer adoption. Develops sales leaders and specialist teams, builds executive relationships, orchestrates Microsoft and partner resources, and drives scaled adoption of Copilot, AI agents, and cloud platforms. Establishes operating rhythms, strengthens competitive positioning, and translates AI transformation opportunities into measurable customer and business outcomes.