Artificial Intelligence Jobs in Cary, NC

Leads Internal Audit assurance and advisory coverage for global cybersecurity, infrastructure, cloud, identity, threat detection, third-party risk, and IT operations. Owns risk assessments, audit planning, execution, reporting, remediation validation, and methodology. Advises CISO and CTO leadership, evaluates AI-enabled security risks and controls, expands analytics and continuous auditing, and develops a global team of technology and cybersecurity auditors. Communicates risk insights to executives, Audit Committee members, and risk committees.

Leads customer insights and measurement initiatives by translating Voice of Customer, behavioral, operational, and business data into actionable recommendations. Defines cross-channel success metrics, governs measurement standards and instrumentation, develops automated dashboards and AI-powered insights, and drives closed-loop feedback processes. Partners with product, technology, operations, and business teams to influence priorities, improve digital experiences, and measure business impact.

Leads enterprise architecture strategy and multi-year roadmaps for US Group domains, embedding generative AI, agentic systems, automation, and Azure cloud capabilities. Oversees modernization, integration, architecture governance, standards, and secure scalable solutions across legacy and cloud environments. Advises executives, influences technology decisions, mentors architects and engineers, and ensures AI initiatives produce measurable business value in a regulated enterprise.

Develop and support enterprise AI applications under senior engineering guidance. Responsibilities include building AI components with Python or C#/.NET, retrieval-augmented workflows, conversational Microsoft Teams experiences, REST integrations, deployments, infrastructure automation, model and prompt validation, observability, documentation, and Agile collaboration. The role emphasizes responsible AI, security, privacy, human-in-the-loop design, and learning established engineering practices.

Leads the design and implementation of MetLife’s AI-first delivery practice. Runs AI delivery pilots, develops context libraries and agentic coding patterns, establishes spec-driven development and review standards, creates reusable enablement assets, and enables teams across GitHub Enterprise and CI/CD tooling. Partners with DevSecOps, Platform Engineering, Architecture, and Learning & Development to address toolchain gaps, measure engineering effectiveness, build practitioner networks, and scale adoption in a governed enterprise environment.

Designs, develops, and maintains scalable .NET applications and AI-powered business solutions. Responsibilities include building web applications and REST APIs, integrating Azure AI services, implementing authentication and secure secrets management, collaborating with architects and stakeholders, troubleshooting production issues, and supporting Agile delivery. The role also emphasizes responsible AI, application governance, performance, documentation, and technical knowledge sharing.

Designs and delivers enterprise data and AI capabilities from concept through production. Responsibilities include defining target architectures, evaluating build-versus-buy decisions, building hands-on data and AI solutions, reviewing code and models, guiding platform adoption, and advising executive stakeholders. The role covers machine learning, generative AI, RAG, agent architectures, semantic layers, MLOps, model governance, cloud data platforms, and production readiness in a regulated environment.

Leads enterprise internal audit coverage for data engineering, data governance, data science, AI risk, AI platforms, tools, and automation. Conducts risk assessments, advisory and assurance reviews, and control evaluations; establishes audit guidance for regional teams; communicates findings and recommendations to senior stakeholders; and supports Audit Committee reporting on enterprise data and AI risks.

Lead end-to-end implementation and management of an AI Technician Assist platform for heavy equipment service operations. Responsibilities include ERP and data integration, AI output validation, technician workflow design, pilot rollouts, training, change management, adoption tracking, and stakeholder communication. The role bridges AI product teams, ERP service data, and field and shop technician workflows to improve diagnostic accuracy, repair efficiency, first-time-fix rates, and platform adoption.

Develops end-to-end core-system features, including AI-enabled functionality, testing, backend architecture, production monitoring, customer escalation management, code reviews, and collaboration with product managers to translate business requirements into scalable technical solutions.

Build AI agents, tools, data connectors, and multi-step workflows using Python, APIs, SQL, and agent frameworks. Develop retrieval strategies, evaluation sets, documentation, and weekly demonstrations for business users. Work in sandbox and read-only environments with human approval required for live-system changes. The intern must be enrolled in a relevant U.S. degree program and available for continued part-time remote work after the summer.

Build AI agents, tools, and data connectors in Python using APIs and SQL. Design multi-step LangGraph workflows with human approval, select appropriate retrieval methods, evaluate answer quality, deliver weekly demonstrations, use AI coding assistants responsibly, and document implementations. The intern will work onsite or hybrid in Cary, North Carolina and may continue part-time remotely for approximately six months after summer.

Develop AI and machine learning software on an agile Scrum team supporting mission-critical systems. Apply optimization, signal processing, control theory, probabilistic modeling, neural networks, classifiers, and dimensionality reduction. Build and deploy algorithms using high-level programming languages, version control, and potentially containerized, distributed, embedded, GPU-enabled environments. The role is fully onsite in Morrisville, North Carolina, with a 9/80 schedule and approximately 10% travel.

Develop AI and machine-learning software on an agile Scrum team supporting mission-critical systems. Apply optimization, signal processing, control theory, probabilistic modeling, neural networks, classification, and dimensionality-reduction techniques. Program primarily in MATLAB, Python, or R, use Git for version control, and potentially deploy solutions with Docker, Kubernetes, Linux, embedded systems, and GPU programming. The role is fully onsite in Morrisville, North Carolina, follows a 9/80 schedule, requires U.S. citizenship, and requires obtaining a Top Secret/SCI clearance with a counterintelligence polygraph.

Leads growth strategy, product-market fit, commercialization, and ecosystem partnerships for AI infrastructure and networking products. Develops market analyses, pricing models, business cases, and partnership frameworks across hyperscalers, data centers, colocation providers, OEMs, and infrastructure companies. Collaborates with engineering, finance, legal, sales, and executives to launch and scale fiber, optical, interconnection, and programmable network services. Tracks pipeline, contracts, revenue conversion, and partner performance.

Leads enterprise AI-first technology delivery transformation at MetLife. Defines operating models, roadmaps, governance, controls, adoption strategies, delivery metrics, and readiness practices for agentic software development. Partners with CIO organizations, DevSecOps, Platform Engineering, Architecture, Risk, Audit, and Legal to implement traceable, reviewable AI-assisted workflows in a regulated environment. Advises senior leaders, resolves cross-organizational ambiguity, and drives initiatives through measurable adoption and business value realization.

Designs and maintains MetLife Global Technology’s AI-first operating model, including team archetypes, role and accountability frameworks, human-agent governance, lifecycle architecture, decision rights, and transition plans. Collaborates with technology, risk, audit, architecture, and delivery leaders to create standards and reference artifacts that support adoption across CIO organizations. The role also facilitates implementation, incorporates field feedback, and evaluates operating-model effectiveness in regulated technology environments.

Define and govern enterprise AI and agentic security architecture. Build controls for agent permissions, tool access, inter-agent trust, LLM threats, AI asset visibility, Shadow AI discovery, and AI security posture management. Embed automated security benchmarks throughout AI development and deployment pipelines, establish enterprise standards, review AI designs, and partner with platform engineering, MLOps, DevOps, IAM, and architecture teams to enable secure, compliant AI adoption.

As Lead Auditor for Data and AI at MetLife, you'll assess risks, lead audits, identify issues, and communicate findings on innovative initiatives.

Leads the strategy, architecture, development, and commercialization of AI-powered network automation products and enterprise services. Designs AI gateways, routers, token services, MCP integrations, semantic caching, and agentic infrastructure across cloud, edge, data center, and NeoCloud environments. Drives proof-of-concepts, performance benchmarking, product roadmaps, market analysis, commercial models, SLAs, security frameworks, and go-to-market strategy for autonomous network capabilities.

Ph.D. interns apply machine learning and AI to semiconductor chip design or enterprise engineering tools. Responsibilities include developing ML models for EDA automation, placement, timing, power, and verification, or deploying LLM, RAG, and agentic systems. Interns will train, evaluate, and deploy models, conduct rigorous experiments, collaborate with engineering and technology stakeholders, assess production performance and safety, and present findings to leadership. The role requires doctoral research in AI, machine learning, computer science, electrical engineering, data science, or a related field.

Lead design and governance of AI-enabled development platforms and agent frameworks for citizen and associate developers. Define reference architectures, reusable patterns, guardrails, and embedded controls for security, compliance, explainability, and resiliency. Partner with engineering, security, and platform teams to validate solutions, drive adoption, and enable reuse through templates, components, and training.

Two-year international rotational program for early-career engineers working across R&D teams on software and AI solutions. Responsibilities include developing innovative network and communications products, collaborating with Agile teams, communicating design and project progress, resolving issues, learning new technologies, and adapting to changing priorities. Participants may complete temporary assignments in other countries or locations before continuing their careers with VIAVI.

Develop and maintain high-quality technical manuals, guides, specifications, and related documentation. Lead information sessions with subject matter experts, align content with user needs and product requirements, improve existing materials, manage documentation projects, incorporate usability-testing feedback, and coordinate with design teams on visuals and diagrams. Apply documentation tools, industry standards, and best practices to improve clarity, usability, and content quality.

Embed with strategic semiconductor customers to deploy LLM- and agent-based AI into end-to-end EDA flows (RTL through signoff). Architect agentic workflows, integrate Cadence AI products, define KPIs for productivity and ROI, guide secure LLM access and infrastructure, run design reviews, and produce reusable playbooks to scale deployments across sites.