Top Artificial Intelligence Jobs

Leads and mentors AI/ML engineers while contributing hands-on to machine learning development. Responsibilities include building data pipelines, training and deploying models, designing scalable ML systems, conducting code and model reviews, applying LLMs and deep learning, guiding technical strategy, managing performance, hiring, and overseeing project delivery. The role requires active TS/SCI clearance and expertise in Python, machine learning frameworks, MLOps, software development, and advanced AI/ML algorithms.

Develop and implement machine learning algorithms across computer vision, natural language processing, time-series, graph data, reinforcement learning, and large language models. Analyze large multi-domain datasets, apply current research, document solutions, and support AWS-based training and deployment pipelines. Mentor team members and collaborate within interdisciplinary teams. The role requires substantial AI/ML development experience, strong Python and ML library skills, and an active TS/SCI clearance.

Lead researchers and developers in creating computer vision AI/ML solutions for remote sensing, including automatic target recognition and multimodal EO/SAR data fusion. Analyze datasets, research supervised and unsupervised approaches, train and optimize deep learning models, deploy them to cloud environments, communicate technical findings, and produce documentation. The role requires technical leadership, customer collaboration, and an active TS/SCI clearance.

Develop and implement AI/ML algorithms across computer vision, NLP, time series, reinforcement learning, and large language models. Analyze multimodal datasets, apply research findings, document systems, support AWS-based training and deployment pipelines, and mentor team members. The role requires substantial AI/ML development experience, advanced Python and machine learning library proficiency, deep learning expertise, and an active TS/SCI clearance.

Develop and implement AI/ML algorithms for defense and commercial applications, analyzing image, text, and graph datasets to build actionable models. Use cloud services to train and deploy models, apply statistical and machine learning techniques, review research, and create technical documentation. The role involves collaboration with software developers and researchers and requires an active TS/SCI clearance with CI Poly.

Leads researchers and developers in building computer vision AI/ML solutions for remote sensing, including automatic target recognition and multimodal EO/SAR data fusion. Responsibilities include preparing datasets, researching supervised and unsupervised methods, training and optimizing deep learning models, deploying algorithms to cloud environments, communicating technical findings, and documenting systems. The role requires active TS/SCI clearance and provides technical leadership from prototype through operational deployment.

Own end-to-end applied research on business ontologies, knowledge graphs, semantic layers, and AI agents over enterprise data. Develop methods using schema matching, entity resolution, LLMs, graph neural networks, and relational models; build benchmarks, evaluation systems, and prototypes adopted by product teams. Collaborate with universities, publish research or open-source work, communicate findings clearly, and mentor interns. The hybrid Palo Alto role requires up to 10% travel.

Build and maintain AI-powered workflows, agents, automations, internal tools, and production systems for creative ideation, copy generation, video pipelines, reporting, and client delivery. Integrate LLMs and third-party APIs, ship rapidly, iterate based on real usage, and develop practical tools that improve marketing operations.

Lead strategic success and adoption for a portfolio of higher-education and government Workday customers. Build C-level relationships, drive deployment and post-production adoption, position upsell opportunities, create Success Plans, resolve escalations, and coordinate internal and partner teams to ensure customer satisfaction, subscription retention, and revenue growth. Advocate product value, guide complex multi-institution deployments, and enable customer self-sufficiency.

Leads the strategy, processes, and AI-native systems that personalize sales and sales development enablement by role, tenure, segment, industry, and region. Builds apps, agents, skills, content, and automated workflows; partners with global and regional enablement teams; pilots and iterates programs; establishes metrics and operating cadence; and influences senior sales leaders to improve ramp time, seller productivity, pipeline, and win rates.

Leads enterprise integration strategy and establishes a modern software engineering function. Oversees APIs, EDI, event-driven architecture, cloud-native applications, AI agent integration, DevSecOps, and operational excellence. Builds and manages engineering, architecture, and EDI teams while defining technology standards, delivery practices, governance, and operating models. Partners with business and technology leaders to deliver secure, scalable integrations and AI-enabled solutions across SAP, Snowflake, Salesforce, Workday, customers, and suppliers.

Build complete applications, workflow automations, and basic AI agents by directing AI coding agents. Translate customer needs into specifications, deploy full-stack solutions, instrument usage and outcomes, evaluate AI-generated work for security and reliability, engage with customers, and document effective prompts and development patterns.

Build complete applications, workflow automations, and basic AI agents using AI coding agents. Translate customer needs into specifications, deploy solutions, instrument usage and outcomes, evaluate AI-generated output for security and quality, engage with customers, and document effective prompts and development patterns.

Join Celonis’s 12-month Orbit Program as an Associate Value Engineer. Consult customers, identify business challenges, build AI and machine-learning prototypes, develop SQL and PQL data models, lead proof-of-concept projects, present solutions to executives, quantify ROI, and establish trusted customer relationships. The role combines technical analytics, enterprise software consulting, customer engagement, and value realization, with mentorship and training provided.

Own product development for Elixir-based applications, translating client needs into specifications and delivery plans. Design architecture, APIs, data models, integrations, scalability, security, and maintainability. Direct AI coding-agent workflows, review generated work, write code when needed, and ensure testing, CI, QA, and controlled releases. Communicate proactively with clients, troubleshoot complex issues, and improve agent harnesses, engineering standards, observability, and quality gates.

Develop and execute the organization’s AI strategy, roadmap, policies, and responsible-use guidelines. Evaluate and implement AI solutions, measure business impact, establish governance for privacy and security, and identify opportunities to improve productivity. Educate employees on AI capabilities, prompting, and responsible use while partnering with technical and nontechnical teams to drive adoption. The role is onsite in Des Moines and requires travel to regional construction jobsites several times monthly.

Train employees on enterprise AI tools, build reusable Claude skills, prompt templates, and agentic workflows, and connect systems through MCP connectors. Pilot and scale AI solutions, manage training and knowledge libraries, support an AI champions network, measure adoption, and enforce AI governance, privacy, security, and access policies.

Lead applied AI research focused on learning business ontologies, semantic layers, and knowledge graphs from enterprise data. Develop graph and relational foundation models, LLM systems over structured data, grounded agents, evaluation benchmarks, and governed business actions. Define research directions, collaborate with universities and SAP product teams, publish results, ship prototypes into products, mentor scientists, and continue hands-on experimentation and coding.

Develop production-ready generative AI and machine learning solutions, including autonomous AI agents using LLM frameworks. Collaborate with data scientists, engineers, MLOps, DevOps teams, and business stakeholders to integrate scalable, reliable, compliant AI systems. Build models, pipelines, monitoring capabilities, and large-scale ETL processes while supporting responsible AI practices and communicating results through reports, projections, models, and presentations.

Set technical direction for Root’s AI platform, including infrastructure, tooling, shared services, governance, reliability, security, observability, and cost management. Lead cross-team initiatives, guide AI and LLM architecture decisions, establish operating standards, shape technical roadmaps, resolve complex tradeoffs, and mentor engineers and technical leaders across the organization.

Owns the architecture, engineering, operation, and roadmap of a secure AI research platform. Builds scalable CPU/GPU cloud infrastructure, self-service research environments, platform automation, CI/CD, orchestration, and infrastructure-as-code. Partners with AI researchers to enable LLM, agentic AI, retrieval, inference, and benchmarking workloads, while maintaining reliability, observability, security, cost controls, incident response, and operational readiness in a regulated enterprise.

Partners with enterprise sales teams to advise CIOs and technical executives on AI architecture, governance, security, integrations, and revenue workflows. Designs reference architectures, technical roadmaps, validation plans, and business cases for Gong’s AI platform, while addressing build-versus-buy decisions and enterprise risk. Leads executive workshops, technical reviews, proofs of concept, and complex pursuits; enables Solutions Engineers through reusable assets and thought leadership; and provides market feedback to Product and Engineering.

Lead the architecture and evolution of enterprise developer telemetry and real-time data platforms. Build scalable streaming pipelines, AI inference capabilities, data lake solutions, observability frameworks, and privacy controls. Correlate AI engineering metrics with business outcomes while mentoring engineers, shaping technical strategy, evaluating build-versus-buy decisions, and contributing directly through prototypes, code patterns, and reusable data products.

Design, develop, deploy, and optimize production AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, and model evaluation. Lead architecture, cost-performance governance, technical reviews, and long-term roadmap development. Apply advanced optimization techniques to improve scalability, latency, throughput, hardware utilization, and inference costs while ensuring responsible AI standards. Mentor senior technical leaders and collaborate with engineers, scientists, technical program managers, and product managers.

Design, build, and operate production agentic AI services for Azure support and diagnostics. Responsibilities include developing LLM orchestration and RAG systems, writing C# and Python, creating evaluation frameworks, integrating Azure services, implementing secure AI patterns, operating reliable production services, and measuring customer impact. The role also provides technical leadership, mentors engineers, and collaborates across product, research, engineering, and support teams.