llm-orchestration jobs in San Diego

Lead enterprise AI platform strategy and execution at a biotech company, driving end-to-end program delivery across engineering, data, cybersecurity, and product teams. Own platform health, KPIs, and telemetry; establish governance, safety guardrails, and regulatory compliance for AI-enabled solutions in a regulated environment.…See more Define multi-year AI roadmaps, coordinate cross-functional dependencies, and orchestrate Agile delivery while partnering with legal, compliance, and tech enablement to ensure scalability, security, and enterprise adoption.

Cloudflare seeks a Senior Customer Engineer to serve major accounts in the Southwest, acting as a trusted technical advisor on enterprise network and security architectures. The role combines deep consultative skills with hands-on technical expertise across Internet fundamentals, security, performance, and developer platforms—translating complex technical concepts into business outcomes for both engineering teams and C-suite executives.…See more The engineer will demonstrate architectural breadth in at least four domains (OSI layers, BGP, WAF, Zero Trust, caching, AI/LLM workflows, scripting, or cloud-native development) and drive customer adoption through technical enablement, custom integrations, and solutions design. This is a quota-carrying, revenue-aligned customer-facing role requiring exceptional communication, SaaS business acumen, and the ability to navigate full-lifecycle enterprise sales cycles.

Chief AI Subject Matter Expert leading the development of intelligent data processing pipelines, NLP systems, and AI-enabled dashboards for defense applications. The role requires 15+ years of experience with generative AI, LLMs, and agent-based development workflows, including hands-on use of tools like GitHub Copilot and Claude for code generation and automation.…See more Responsibilities include prototyping emerging AI tooling, mentoring engineering teams on AI integration, designing secure production AI solutions, and identifying opportunities to accelerate the software lifecycle through AI and automation. Must demonstrate expertise in LLM APIs, RAG architectures, vector databases, prompt engineering, and AI-specific security considerations in classified/sensitive environments.