Top Artificial Intelligence Jobs in Raleigh-Durham, NC

Design and implement security across infrastructure, applications, data, and AI systems. Own authentication, authorization, tenant isolation, secure log ingestion and querying, and AI security risk mitigation. Lead security incident response and postmortems, establish practical security practices, and partner with engineering to integrate security into development. The role requires application or infrastructure security experience, knowledge of OWASP vulnerabilities, and experience securing distributed systems and APIs.

Owns Xint’s technical content and developer relations strategy for application security practitioners. Conducts and publishes original security research, creates technical tutorials and demonstrations, supports conference talks and webinars, and engages practitioner communities. The role requires hands-on understanding of vulnerabilities, exploit reproduction, security tooling, and AI-assisted security, along with strong technical communication and public speaking skills.

Lead technical enablement for resellers, distributors, MSSPs, and system integrators. Train partner teams, support partner-led sales, run demos and proofs of concept, create technical enablement assets, answer security reviews and RFPs, and provide product feedback. Collaborate with Channel Sales, Sales Engineering, Product, Marketing, and Engineering while representing the company at partner events and customer briefings. Travel is required for partner and customer engagements.

Evaluate and improve the safety, security, and robustness of large language models. Responsibilities include designing jailbreak, prompt injection, adversarial, and tool-use abuse tests; developing regression suites and evaluation frameworks; identifying vulnerabilities; translating findings into safety recommendations; and documenting methodologies and results for technical and non-technical stakeholders.

Design, develop, debug, and optimize LustreFS across client, metadata, object storage, networking, and backend layers. Investigate customer and scale-related defects, perform root-cause analysis, improve reliability and performance, review code and designs, collaborate with QE and support, create diagnostics and documentation, and use AI-assisted tools to accelerate triage and engineering workflows.

Own the cryptographic core: select and evolve MPC/TSS schemes, author protocol reviews, implement and review Rust/Go production crypto, lead audit responses, prepare incident fixes, publish and represent externally, and teach/mentor engineers while scaling the crypto function.

Build and operate production AI and LLM systems for safety-critical enterprise applications. Responsibilities include multi-step agent orchestration, retrieval across Neo4j and vector stores, evaluation frameworks, model comparison, observability, quality monitoring, failure handling, and production incident response. The role requires strong Python and experience with asynchronous services, LLM workflows, evaluation, retrieval, graph reasoning, and enterprise AI security. It also contributes to model selection, technical direction, and the AI roadmap.

Own top-of-funnel recruiting for engineering and product roles by sourcing, engaging, and pipelining candidates across AI/ML, full-stack, backend, infrastructure, and data engineering. Maintain candidate records and outreach activity in Ashby, collaborate with recruiters on priorities, and use AI tools and automation to improve sourcing workflows during a three-month contract.

Own Stay AI’s marketing function end to end, including competitive positioning, product marketing, sales enablement, content, channel strategy, market narrative, pipeline generation, and executive reporting. The role partners closely with sales, product, and the CEO, creates messaging and marketing materials directly, supports product launches, analyzes campaign performance, and presents marketing results to leadership and the board.

Build and maintain Python backend services and AI-assisted applications for threat investigations. Partner with investigators, integrate APIs and AI capabilities, troubleshoot production issues, improve reliability and observability, and participate in rotating on-call coverage. Own engineering solutions from requirements through deployment and ongoing support, including work across backend services, data pipelines, asynchronous workflows, and platform operations.