Top Artificial Intelligence Jobs

Leads the practical application of generative and agentic AI across the firm. Partners with business and technology stakeholders to identify opportunities, design secure and scalable AI architectures, evaluate technical tradeoffs, develop reusable patterns, and guide solutions from discovery through production. Provides architectural standards, prototypes, evaluation methods, and engineering handoff support while ensuring alignment with security, data, operational, cost, and business requirements.

Build and operate AI-driven systems that improve the reliability, compliance, and observability of Disney’s streaming infrastructure. Develop agentic AI systems, predictive models, anomaly detection, APIs, telemetry pipelines, root-cause analysis tools, and automated compliance guardrails. Deploy scalable cloud-native services, contribute to architecture and production ownership, and collaborate with engineering, product, and platform teams to integrate intelligence into incident response and operational workflows.

Build backend services, data pipelines, evaluation frameworks, APIs, metrics layers, and dashboards for operational AI and observability tools. Measure model precision, recall, drift, alert accuracy, incident correlation, and business impact using telemetry, logs, and user feedback. Partner with SRE, DevOps, product, and platform engineering teams to improve AI reliability, reduce alert noise, and support model improvement across Disney streaming properties.

Lead the architecture, build, and deployment of AI-driven automation and intelligent systems to solve security, compliance, and risk challenges. Develop real-time intelligence, workflow automation, and risk-based decision-making tools, and engage customers and partners to refine and deploy production-grade solutions.

Designs and delivers production AI solutions addressing business and customer problems. Responsibilities include gathering requirements, architecting AI agents, tools, retrieval systems, integrations, and interfaces; building prototypes; using AI coding tools; defining testing and success metrics; and collaborating with Product, UX, SRE, QA, and Software Development teams.

Prototype and develop generative AI applications for business software, including automated model evaluation, synthetic video, and consistent image and brand asset generation. Own projects from experimentation through product delivery, combining system architecture, quantitative reasoning, product judgment, and creative LLM application development.

Design and deliver scalable, safe conversational AI agents for regulated environments. Coordinate multiple agents, monitor production traces, create evaluation cases, improve agent frameworks, integrate external data sources, and support consistent conversations across voice, text, and email. The role requires hands-on experience shipping conversational agents and AI applications at scale, plus evaluation and tracing infrastructure experience.

Supports AI-enabled automations, integrations, prompt and workflow design, and Claude Enterprise administration while assisting with SharePoint Online and NetDocuments administration. Responsibilities include provisioning, permissions, governance, documentation, Microsoft 365 support, scripting, Power Automate flows, and tier-1/tier-2 issue resolution. The role is designed for an early-career professional with 0–2 years of experience and offers development toward AI engineering or platform administration.

Lead cross-functional Front End semiconductor manufacturing initiatives focused on cost reduction, productivity, factory output, and operational efficiency. Define program scope, timelines, resources, dependencies, and metrics; manage risks and roadblocks; improve business processes and reporting; and communicate results to senior leaders. Apply data analytics, AI, automation, and digital solutions to deliver measurable manufacturing and business improvements.

Conduct original research in deep learning, Transformers, time-series foundation models, and quantitative finance. Develop and evaluate predictive models using large-scale financial datasets, partnering with quantitative researchers, traders, and engineers on forecasting, alpha generation, liquidity, execution, and portfolio applications. Lead end-to-end research, create reproducible research assets, mentor junior staff, communicate findings to stakeholders, and follow model-risk, data-governance, privacy, ethics, and responsible-AI standards.

Leads architecture and cross-service execution for Cisco’s distributed AI platform. Responsibilities include designing multi-service systems, authoring technical specifications, implementing identity and zero-trust security, managing CVE remediation and production triage, and mentoring senior engineers. The role requires extensive experience with Go, Python, distributed systems, authentication, agentic AI, Kubernetes, observability, and cloud infrastructure.

Build and maintain API integrations, data pipelines, web applications, and AI-powered solutions using LLM APIs. Support databases, deployments, debugging, testing, authentication, and application security. Improve UI/UX, evaluate AI-generated outputs, investigate emerging technologies, and contribute to workflow improvements. The role is suited to current students, recent graduates, or candidates with equivalent practical experience and emphasizes hands-on AI development, collaboration, and continuous learning.

Build and deploy computer vision models for live and recorded video feeds. Responsibilities include curating and annotating datasets, training and tuning YOLO models, processing video with Python, developing inference pipelines, evaluating model performance, and delivering production-ready code in an Agile environment. The role supports a federal border security mission and requires onsite work in Ashburn, Virginia, U.S. citizenship, and successful completion of a CBP background investigation.

Leads the design, development, and production deployment of AI solutions for healthcare payer applications. Responsibilities include architecting AI models and integrations, developing scalable production systems, evaluating model accuracy and fairness, translating business workflows into AI-enabled automation, researching emerging techniques, advising stakeholders, and mentoring junior engineers.

Supports responsible enterprise AI adoption by documenting use cases, engaging users, analyzing usage and feedback, developing enablement materials, testing prompts and workflows, and communicating recommended practices. The intern creates dashboards and presentations, evaluates AI program impact, promotes safe AI use, and assists with strategic projects under mentorship.

Owns the implementation, hardening, tuning, and polish of game AI behaviors and systems for shipping quality. Collaborates with design, animation, and other disciplines to create believable enemy behavior and strong player experiences. The role requires expertise in Unreal Engine, modern game AI architecture, animation systems, and C++, along with experience shipping at least one game focused primarily on AI, preferably a AAA action or FPS title.

Own enterprise AI platform integrations, including identity, connectors, APIs, provisioning, and control-plane guardrails. Lead AI support, user onboarding, enablement, technical escalations, stakeholder relationships, and vendor partnerships. Establish support tiers, SLAs, runbooks, observability, governance evidence, and risk-review processes. Partner with application development teams on platform handoffs, manage entitlements and decommissioning, and guide adoption across high-touch business groups.

Leads enterprise agentic AI strategy, architecture, and delivery. Builds scalable AI platforms, foundational services, frameworks, evaluation pipelines, model gateways, and observability capabilities. Manages and mentors AI engineering teams, partners with architecture, security, data, DevOps, and product leaders, and establishes engineering practices for reliable, secure, cost-effective AI deployment.

Design, build, deploy, and optimize AI/ML and generative AI solutions on Databricks. Develop scalable Spark and Delta Lake data pipelines, operationalize models with MLflow, and build RAG and LLM applications. Implement MLOps practices including CI/CD, monitoring, governance, and model deployment. Collaborate with technical, data, engineering, and business teams to deliver enterprise-scale AI platforms and analytics solutions.

Develop and scale AI, Microsoft Copilot, Power Platform, and intelligent automation solutions across Buildings. Responsibilities include designing AI agents and workflows, identifying automation opportunities, delivering training and adoption programs, supporting governance, integrating Microsoft platforms, and measuring business value through analytics and reporting.

Technical Lead responsible for architecting, deploying, operating, and sustaining secure agentic AI, LLM inference, data, and platform capabilities across classified and unclassified environments. Responsibilities include JWICS hosting, cross-domain data flows, cloud architecture, observability, security hardening, integration and performance testing, troubleshooting, documentation, accreditation support, and technical leadership. The role is onsite at the Pentagon and requires routine domestic and international travel.

Analyze structured and unstructured data from multiple sources; identify patterns, risks, and actionable insights; support LLM, RAG, NLP, and Generative AI applications; develop prompts; evaluate AI outputs; prepare and validate data; create reports and visualizations; and apply data governance, security, privacy, and responsible AI practices.

Build and support production AI platform capabilities for PlayStation’s digital commerce ecosystem. Develop LLM-powered services, reusable components, scalable APIs, microservices, and event-driven workflows using Python or Java. Collaborate with stakeholders to identify and prototype AI use cases, measure outcomes, and productionize successful solutions. The role emphasizes reliable, secure, cost-efficient backend engineering and practical applied AI, including integrations with model APIs, business workflows, data, documents, and internal services.

Designs scalable technical solutions for Intelligence Community and Department of War contract opportunities. Partners with customers, business development, engineering, and leadership to assess mission requirements, produce system architectures and operational workflows, develop prototypes and demonstrations, and create technical proposal content. The role requires expertise in cloud and hybrid infrastructure, AI integration, networking, security, compute, and storage, along with strong communication and customer engagement skills.

Design, build, and deploy AI-driven products, agentic systems, and end-to-end workflows for commercial real estate users. Own features from user discovery through architecture, implementation, and deployment. Develop evaluation frameworks, optimize context management and retrieval, translate domain expertise into technical requirements, and continuously benchmark emerging LLM models and agentic frameworks.