Top Artificial Intelligence Jobs

Own the full enterprise sales cycle for cybersecurity solutions across named organizations with 5,000+ employees. Build pipeline through outbound prospecting, relationships, events, and partners; engage CISOs and security teams; lead technical evaluations; develop account plans and business cases; navigate security, privacy, legal, and procurement processes; forecast accurately; and provide customer insights to improve product strategy and sales execution.

Provides high-level administrative support to senior executives by managing correspondence, calendars, meetings, travel, expenses, projects, events, business reporting, and cross-functional coordination. Maintains critical organizational documents, prepares quarterly business reviews, tracks action items, and improves executive support systems and processes. Requires strong prioritization, communication, business judgment, multitasking, and project coordination skills.

Provides advanced technical application guidance, integration, troubleshooting, and optimization for industrial machine-vision solutions. Works with Cognex products, PLCs, controllers, optics, lighting, robotics, motion control, and automation equipment. Supports Sales with customer-facing technical expertise, conducts onsite trials, creates documentation and training, mentors applications engineers, and provides product feedback. Requires industrial-environment work, on-call flexibility, and travel up to 50%.

Supports customers with complex machine vision applications, product integration, troubleshooting, onsite optimization, trials, and technical solutions. Integrates Cognex products with PLCs, PCs, and controllers; advises Sales; documents findings; provides training; mentors applications engineers; and delivers customer feedback to product teams. Requires advanced knowledge of image processing, optics, lighting, industrial communications, programming, controls, robotics, and automation. Travel may reach 50%, with occasional evening, weekend, and on-call support.

Deploy machine learning algorithms and conduct AI/ML model testing and evaluation. Apply software engineering expertise and advanced knowledge of multiple programming languages to support high-performance computing, large-scale data analytics, and cutting-edge information technology solutions. An active TS/SCI clearance with polygraph is required.

Designs and implements machine learning models, data-mining methods, advanced analytical algorithms, statistical analyses, artificial intelligence solutions, and data-analysis software. The role requires extensive experience developing descriptive, predictive, and prescriptive analytics, analyzing datasets, and performing software or cloud development. An active TS/SCI clearance with polygraph is required, along with a quantitative degree or qualifying equivalent experience.

Lead Mirage’s Product Design function by setting design vision and quality standards, managing and developing designers, and building the team, systems, and culture. Partner with executive, Product, and Engineering teams on product strategy and roadmap. Guide complex AI-native video creation experiences from exploration through launch, translating emerging capabilities across text, image, audio, motion, and video into intuitive products.

Develop and deploy foundational AI systems, including LLM inference, foundation model training, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Optimize AI systems for cost, latency, throughput, scalability, and hardware utilization. Architect multi-model orchestration pipelines, establish technical standards and governance, lead design reviews, contribute to long-term AI roadmaps, and mentor senior AI engineering staff.

Design, develop, deploy, and support foundational AI systems, including large language model inference, foundation model training, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize AI systems for scalability, cost, latency, throughput, and hardware utilization. Own complex system architectures, define reliability objectives, lead technical reviews, ensure security and compliance, and mentor engineering colleagues.

Design, develop, deploy, and support foundational AI systems, including foundation model training, LLM inference, agents, similarity search, guardrails, evaluation, governance, and observability. Optimize AI infrastructure for cost, latency, scalability, throughput, and hardware utilization. Own complex system architecture, define reliability objectives, lead technical reviews, ensure security and compliance, contribute to long-term AI roadmaps, and mentor engineering talent.

Build and optimize foundational AI systems, including LLM inference, agentic workflows, vector search, model evaluation, guardrails, and orchestration pipelines. Lead cost-performance governance, improve model scalability and hardware utilization, shape technical roadmaps, establish AI engineering standards, and mentor senior technical staff. The role requires applying current AI research to reliable, responsible production systems across cloud and large-scale infrastructure.

Conduct applied research and develop large-scale AI foundation models, particularly LLMs, optimization methods, and fine-tuning techniques. Responsibilities include designing, training, evaluating, validating, and deploying models; optimizing training and inference at scale; collaborating with data scientists, engineers, and product managers; translating research into business applications; and producing technical reports or conference publications.

Supports government and critical-infrastructure customers with cybersecurity architecture, systems engineering, requirements development, technology evaluation, and cyber operations analysis. The role documents architectures, identifies capability gaps, develops mission workflows, and supports Zero Trust and cyber resilience strategies. Responsibilities also include evaluating AI and machine-learning techniques, piloting technologies, transitioning solutions into operations, presenting technical topics, and collaborating with stakeholders and subject matter experts.

Leads cybersecurity assurance engagements for government, defense, and critical infrastructure partners. Develops security frameworks, risk measurements, controls, policies, technical guidance, and training focused on cybersecurity and operational resilience. Applies audit and assessment methodologies, NIST and ISO standards, continuity planning, and technology risk management. Leads multidisciplinary projects, advises customers, presents research, mentors team members, and contributes to applied research on emerging cybersecurity challenges, including artificial intelligence and resilient systems.

Conduct prospect identification, wealth screening, and donor research for major and principal gift fundraising. Analyze advancement and constituent data, create prospect profiles, dashboards, and reports, maintain Raiser's Edge data integrity, and establish scalable screening and prospect-management processes. The role collaborates with gift officers, Advancement leadership, Information Technology, and Advancement Services while supporting data migration, enrichment, deduplication, and workflow improvements through technology and automation.

Own strategic and technical transformation engagements for enterprise clients using Pencil’s Generative AI platform. Lead implementation planning, structured problem-solving, change management, AI process design, stakeholder alignment, and client narratives. Translate client needs into product feedback and repeatable transformation blueprints while ensuring adoption, time-to-value, and post-launch performance.

Own strategic and technical transformation engagements for enterprise clients using Pencil’s generative AI advertising platform. Lead problem structuring, implementation planning, change management, AI process design, stakeholder alignment, and client recommendations. Partner with engineers and creative leads, provide product feedback, ensure adoption and time-to-value, and create repeatable transformation blueprints. The role requires technical fluency, hands-on AI tooling, comfort with ambiguity, senior stakeholder management, and at least five years of relevant experience.

Lead the design, training, fine-tuning, deployment, and monitoring of generative AI, large language model, retrieval-augmented generation, and multimodal systems. Build scalable cloud-based MLOps pipelines, optimize inference, conduct model evaluation and bias assessments, and support responsible AI, security, compliance, and audit readiness. Collaborate with data scientists, platform engineers, and business stakeholders while mentoring junior engineers and translating enterprise use cases into secure operational AI solutions.

Design, build, and deploy production-grade LLM agents, RAG systems, voice/image AI, and automation workflows. Implement TTS/STT and generative image models, develop full-stack APIs/microservices, optimize performance, and ensure security/compliance while collaborating with product and operations teams.

Design, build, and maintain batch and streaming data pipelines on GCP (BigQuery, dbt, Airflow, Pub/Sub). Productionize ML workflows (training, inference, CI/CD) using Cloud Run, GKE, and Vertex AI. Support real-time inference, RAG/LLM assistants, graph-based recommendations, and model monitoring. Collaborate with cross-functional teams to deliver scalable, reliable data products and observability for downstream ML and analytics.

Build and deploy production GenAI systems for enterprise clients in financial services and healthcare. Embed with customers to understand business functions, develop AI solutions using Claude and AWS, create evaluation suites, guide adoption from strategy through deployment, and improve reusable blueprints and delivery frameworks. The role requires hands-on software engineering, cloud-native delivery, presales communication, and autonomous ownership in ambiguous environments.

Build and deploy production GenAI and LLM systems for enterprise clients in financial services and healthcare. Embed with customers to understand operational needs, design AI solutions, own implementation from strategy through deployment, develop evaluation suites, and improve reusable industry blueprints. Advise senior stakeholders, contribute to pre-sales, and help shape AI delivery tooling and frameworks using Claude, AWS, Python, and TypeScript.

Build and deploy production generative AI and LLM systems for financial services and healthcare clients. Embed with client teams to understand business operations, design AI solutions, create evaluation suites, and deliver cloud-native systems on AWS. Lead engagements from strategy through deployment, contribute to AI tooling and blueprints, advise senior stakeholders, and support pre-sales. Work hands-on with Claude, Claude Code, Cowork, integrations, and production engineering practices.

Leads global patient strategy and market development for Dysport in migraine, using patient insights, segmentation, analytics, AI, and journey mapping to improve disease awareness, diagnosis, referral, preventive-treatment consideration, and engagement. Partners with medical, market access, analytics, digital, regional, and local teams; manages agencies, budgets, launches, advocacy, and performance measurement across global markets.

Recruit exceptional talent for Microsoft’s CoreAI division across systems engineering, AI science, and agent-native development. Partner with engineering and product leaders to develop hiring strategies, analyze talent data, build hiring plans, attract and close competitive candidates, and improve candidate experience. Advise stakeholders on talent gaps, influence hiring decisions, optimize recruiting processes, and maintain compliant candidate documentation under OFCCP and GDPR guidelines.