Artificial Intelligence Jobs in Durham, NC

Lead development and validation of LLM inference platforms for NVIDIA edge GPUs. Track open-source framework innovations, analyze model-to-hardware mapping, optimize GPU kernels and multi-node inference, produce performance reports, maintain developer inference recipes, own model bring-up workflows, and support partners on hardware-specific inference issues.

Design and deliver high-performance, area- and power-efficient ASIC/GPU micro-architecture and RTL. Develop agentic AI solutions to craft micro-architecture, implement RTL, and produce fully verified, synthesis/timing-clean designs. Collaborate with designers and tool owners, and build LLM-powered engineering assistants, multi-agent systems, and multi-modal dialogue tools to accelerate chip design workflows.

Lead enterprise AI transformation end-to-end: define strategy, roadmaps, and governance; partner with business and tech leaders to redesign workflows; drive build/buy decisions; manage value realization, adoption, change management, and regulatory compliance; oversee transformation teams and scale AI capabilities across the organization.

Lead enterprise AI transformation from strategy through adoption, partnering with business and tech leaders to redesign workflows, define roadmaps, govern and scale AI capabilities, manage value realization and change management, and ensure compliance and production readiness in regulated healthcare environments.

The role involves researching and developing GPU-accelerated AI workloads, optimizing algorithms, and collaborating with technical experts to improve hardware performance.

Lead a team to optimize algorithms for Deep Learning and Machine Learning, define technical initiatives, and collaborate with various teams for hardware and software innovation.

Owner of Avalara's AI workflow platform (starting with n8n): design, deploy, and operate secure, multi‑environment infrastructure with IaC and CI/CD; embed governance, observability, SLOs, and AI‑enhanced operations; create reusable patterns and mentor teams to raise DevOps and AI maturity.

The AI Resilience Fund Manager will build and manage a fund focused on AI-resilient investments. Responsibilities include developing the investment thesis, raising capital, and advising investors on risk-adjusted strategies for a long-term portfolio.

Support the Corporate AI team by gathering requirements, mapping processes, evaluating AI tools, managing intake and KPIs, and producing clear documentation to turn ideas into measurable AI solutions.

Lead enterprise sales and go-to-market for NVIDIA AI and accelerated computing with Lenovo: develop technical understanding, package joint solutions, co-market/co-sell across channels, build ecosystem partnerships, and drive integration, commercialization, and thought leadership.

Research, design, and implement foundation models for machine-generated and graph data; develop distributed training and inference pipelines; collaborate with engineering and product teams to productionize models; evaluate new AI/ML techniques and drive MLOps, monitoring, and model optimization to improve scalability and reliability.

Lead delivery of core platform capabilities from ideation to launch for an enterprise-scale agentic/AI platform. Author specs, prioritize work, run discovery with customers, partner with engineering, UX, and GTM teams, track OKRs, and ensure successful customer enablement. Operate in a fast-moving, AI-focused product environment and adapt plans as business priorities change.

Lead the end-to-end transformation of a ligand-binding bioanalytical lab to a digitally orchestrated, automated operation. Design and deploy automated workflows, integrate instruments and digital platforms (LIMS/ELN), manage change and validation, lead a multidisciplinary team, define product backlog and agile rhythms, and drive adoption, training, and inspection readiness.

As a Senior Software Engineer focused on AI agents, you'll develop core agent architecture, handle complex workflows, and work with large sales data to automate processes and support the sales cycle.

The Senior AI/ML Applications Engineer will develop, integrate, and support AI-driven tools for IC design and verification, focusing on agentic AI methods to enhance productivity.

Lead design and engineering of enterprise AI-powered automation using n8n as an orchestration platform. Build scalable, secure API-first and event-driven integrations, AI-enabled workflows and agents, CI/CD and governance, observability, and reusable automation frameworks. Provide technical leadership, mentor engineers, and drive platform standards and operational excellence.

Define and drive enterprise AI automation architecture and governance for scalable, secure, API-first and event-driven workflows. Create reusable automation patterns, influence cross-functional roadmaps, mentor engineers, and ensure measurable operational and business outcomes.

Translate complex business workflows into implementation-ready requirements for AI-enabled automation and agentic workflows. Map current/future-state processes, define APIs, triggers, data mappings, acceptance criteria, and governance. Collaborate with AI Automation Engineers, architects, and stakeholders to ensure scalable, auditable, and measurable AI automation solutions and support delivery, testing, and continuous improvement.

Design, build, and operate customer-facing AI systems across the full product lifecycle: discovery, prototyping, deployment, monitoring, and scaling. Translate ambiguous problems into technical specs, partner with product, and ship production-grade AI solutions with attention to maintainability and customer impact.