retrieval-augmented-generation jobs in San Diego

Lead the design, development, and deployment of enterprise-scale Generative AI and LLM solutions across Azure and AWS environments. Define AI architecture frameworks, standards, and governance practices while architecting RAG systems, agentic AI, multi-agent systems, and vector database solutions.…See more Partner with business leaders and engineering teams to translate business requirements into scalable, secure, and responsible AI platforms. Mentor architects and data science teams while evaluating emerging AI technologies and driving innovation initiatives.

Staff-level embedded software engineer responsible for designing and developing AI, GenAI, and multimedia SDKs/frameworks for IoT edge devices (drones, cameras, AI boxes, appliances). The role requires architecting high-performance inference pipelines, multi-stream AI processing, and GStreamer-based plugins for Qualcomm hardware platforms.…See more Must have 5+ years of C/C++ experience in embedded systems, strong knowledge of AI inference frameworks (PyTorch, TensorFlow, ONNX Runtime, LiteRT), GenAI orchestration tools (LangChain, LlamaIndex), and multimedia/HAL integration across Android, Tizen, and Linux. Ownership spans architecture, design, implementation, and deployment of production-quality SDK components.

Principal Engineer leading the technical direction for ServiceNow's Conversational Analytics platform, which enables customers to query data in natural language using AI. The role combines hands-on architecture and prototyping with mentorship of engineering teams, requiring deep expertise in AI/ML systems, vector retrieval, agentic architectures, and knowledge graphs.…See more You'll collaborate with product and leadership to design cloud-based solutions integrating LLMs and AI into enterprise workflows, with accountability for customer success metrics and evaluation frameworks.

Design, implement, and optimize real-time embedded modem firmware across protocol layers and drivers while meeting strict latency, memory, and power constraints. Pioneer AI-native development practices by integrating AI coding agents, LLM-based code review, and automated test synthesis into daily workflows to accelerate delivery and debugging.…See more Own end-to-end feature delivery from requirements through on-target bring-up, and debug complex multi-layer hardware issues using AI-assisted analysis. Requires deep expertise in modern C/C++, embedded systems (DSP/Arm architectures), RTOS internals, data structures, and hands-on target hardware debugging, combined with practical experience using AI coding assistants and agentic tools.

Design and build production AI solutions including copilots, agents, RAG applications, and workflow automations on Azure OpenAI, Claude, and Microsoft platforms. Write custom code in Python, JavaScript/TypeScript, or C# and leverage low-code platforms like Power Automate and Logic Apps where appropriate, following solid engineering practices (version control, testing, CI/CD, AI output evaluation).…See more Integrate solutions with enterprise systems and APIs with security-first design, own projects end-to-end from deployment through adoption and improvement, and work with security, architecture, governance, and compliance teams to ensure production readiness. Communicate clearly to both technical and business audiences, document designs, and coach teammates on AI capabilities, limits, and risks.

Lead the design, deployment, and governance of an enterprise AI platform integrating AWS Bedrock, Microsoft 365 Copilot, and structured/unstructured data sources. Act as the primary technical authority for AI infrastructure, RAG architecture, security controls, and AI adoption across business units, with responsibility for platform budget, vendor contracts, and internal capability building through mentoring and community-of-practice leadership.…See more Requires hands-on production experience with Bedrock (Agents, Knowledge Bases, Guardrails), M365 Copilot enterprise deployment, and proven ability to operate as a solo platform owner in a matrixed organization without direct reports.

Design, develop, and optimize real-time embedded modem software for Qualcomm's cellular platforms (5G/6G), working close to the metal with performant C/C++ on DSP and Arm cores across protocol layers, drivers, and RTOS components. Own end-to-end feature delivery from requirements through on-target validation, with strict latency, memory, and power constraints.…See more Pioneer AI-native development practices by integrating code-generation agents, LLM-based code review, and automated test synthesis into daily workflows to accelerate delivery and debugging. Debug complex multi-layer issues on target hardware, increasingly leveraging AI-assisted log and crash analysis.

The AI Architect will lead the design, development, and deployment of enterprise-scale generative AI solutions across Azure and AWS, partnering with business and engineering leaders to define AI strategy and architecture standards. The role requires deep expertise in modern LLMs (Claude, Gemini, OpenAI), multi-cloud AI platforms, and enterprise architecture, with 10+ years in software/cloud architecture and 5+ years architecting AI/ML solutions.…See more Key responsibilities include designing end-to-end GenAI solutions leveraging RAG, agentic AI, and multi-agent systems; establishing cloud-native deployment patterns; and defining governance, compliance, and responsible AI frameworks. The ideal candidate will serve as a trusted technical advisor to executives, mentor engineering teams, and drive AI adoption through reusable frameworks and reference architectures.

Lead end-to-end development of AI agents and autonomous engineering tools for Teradata's enterprise platform, managing multiple global engineering teams. Shape engineering strategy for agent platforms, LLM gateways, vector stores, observability frameworks, and low-code/no-code/pro-code agent frameworks.…See more Drive architecture standardization, governance practices, operationalization pipelines, and ROI metrics while partnering with product, architecture, and AI platform teams. Requires 12+ years software engineering experience with 5+ years in technical leadership, hands-on expertise with LLMs, agent frameworks, distributed systems, cloud platforms (AWS, Azure, GCP), and modern CI/CD tools.

Staff Software Developer who will design, develop, and maintain AI-enabled knowledge management and decision-support platforms for environmental and engineering applications. Responsibilities include building data ingestion workflows, implementing retrieval-augmented generation (RAG) systems with vector embeddings and semantic search, developing backend services and APIs, creating secure web-based UIs, and working with cloud services (Azure AI Search, Blob Storage, PostgreSQL).…See more The role requires strong software development skills demonstrated through a public code portfolio, familiarity with LLMs and prompt engineering, and the ability to collaborate across technical teams to translate project needs into practical features.