model-selection jobs in San Diego

This role combines prompt engineering expertise with AI system governance and enterprise adoption strategy. The engineer will optimize LLM performance across platforms (OpenAI, Anthropic), design and configure AI agents and chatbots with knowledge grounding, and establish prompt governance frameworks and best practices.…See more Success requires 5+ years in AI/ML systems, 2+ years of hands-on prompt engineering, and demonstrated ability to evaluate AI performance, manage knowledge systems, and guide enterprise clients through AI tool adoption and deployment.

Lead Qualcomm's GenAI transformation for embedded and software engineering, building reusable AI agents, agentic workflows, and developer productivity tools that scale across teams. Partner with platform and engineering teams to establish secure AI practices, governance models, and metrics while serving as a technical thought leader who shapes the organization's transition to AI-native engineering workflows.…See more Requires Principal-level technical leadership with deep expertise in generative AI, LLM-based systems, and hands-on experience deploying GenAI solutions in complex engineering environments. Collaborate on code generation, code review, test automation, and release readiness use cases while driving measurable productivity and quality improvements.

An AI Software Developer at Booz Allen Hamilton will design, implement, and integrate AI-enabled automation and analytics solutions for Navy cybersecurity and mission workflows. The role requires hands-on Python development, API integration, and secure system design in classified or controlled environments, with close collaboration between cybersecurity specialists, engineers, and mission stakeholders.…See more Success demands translating mission requirements into technical tasks, delivering credible implementations (not slide-only recommendations), and operating within RMF, compliance, and secure engineering practices. The ideal candidate combines software engineering rigor (version control, code review, testing) with AI/LLM experience and the ability to work in small, structured teams on multidisciplinary problem-solving.