Top AI Engineer Jobs in Los Angeles, CA

Build and ship end-to-end AI-first product features: extend a Neo4j Brand Knowledge Graph, design predictive optimization and measurement systems, implement LLM orchestration and integrations, develop React/TypeScript frontends and scalable backends, participate in client-facing demos, and own QA and documentation.

Design, develop, and deploy LLM-powered applications and RAG pipelines using Python and LLM frameworks (LangChain, LlamaIndex, Semantic Kernel). Integrate enterprise data, embeddings, vector databases, and knowledge graphs; perform prompt engineering, orchestration, and agent workflows. Evaluate model quality, bias, explainability, and performance. Deploy cloud-native production systems on Azure with Kubernetes and CI/CD, following SDLC and DevOps practices. Must obtain and maintain Secret clearance and bring extensive software development experience (15+ years, 3+ with generative AI).

Lead the architecture, build, and deployment of AI-driven automation and intelligent systems to solve security, compliance, and risk challenges. Develop real-time intelligence, workflow automation, and risk-based decision-making tools, and engage customers and partners to refine and deploy production-grade solutions.

Integrate and fine-tune existing AI models into product features, build evaluation frameworks and observability for production AI, collaborate with data science and engineering, and develop AI-powered application features using Python to improve user experience.

Build and maintain AI platform infrastructure, connectors, API integrations, and custom AI-powered applications. Implement authentication, data pipelines, and tooling to embed LLM capabilities across teams. Contribute code, documentation, reviews, and enablement while ensuring security and compliance for government requirements.

Build and lead an enterprise AI platform: design infrastructure, integrations, and custom AI applications. Own provider/tool selection, deploy production model pipelines and connectors, ensure compliance with government security requirements, mentor engineers, and deliver company-wide AI enablement and training.

Build and operate an enterprise AI platform and integrations that connect LLMs to internal systems. Develop production AI applications, manage model/provider evaluations, ensure security/compliance for government environments, and deliver company-wide AI training and enablement.

Lead design and delivery of production autonomous agents and agentic workflows: architect orchestration, integrate and optimize frontier LLMs, drive model fine-tuning and evaluation, mentor engineers, and translate business goals into safe, reliable, scalable AI-powered product experiences.

Build and operate Coinbase's LLM and agent platform: design the LLM gateway, agent runtime, knowledge bases, AI spend governance, observability/eval tooling, and ship production agents while partnering cross-functionally to ensure secure, cost-effective, and responsible generative AI at scale.

Build and operate Coinbase's LLM and agent platform: unified model gateway, AI Hub, secure microVM agent runtime, knowledge base integrations, AI FinOps, observability and evaluation tooling, and production-grade agent deployments with teams across the company.

The AI Automation Lead will architect and deliver multi-agent AI workflows, develop full-stack applications, and lead technical decisions across engineering teams.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

Design and build LLM-powered agents for hardware product development. Responsibilities include ensuring effective coordination among engineering disciplines and integrating AI systems with existing tools.

Design, build, deploy, and maintain scalable, resilient backend services for a Voice AI platform. Lead cross-cutting projects, make architectural decisions, integrate AI platforms, implement observability and evaluation frameworks, and mentor engineers.

Join Capsule as an AI Engineer to develop ML models for video editing. Responsibilities include researching ML techniques, collaborating on feature development, and optimizing model performance.

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.

As a Senior AI/Data Engineer, you will design and maintain scalable data and AI infrastructures, partnering with cross-functional teams to deliver reliable data systems and support AI-driven business capabilities.

As an AI Creative Technologist, you will architect AI-enhanced solutions, collaborate with various teams, and serve as the technical point of contact for partners, integrating LTX technologies into production pipelines.

Develop AI solutions for marketing teams, integrating AI agents and workflows while coaching teams for self-sufficiency in AI use.

As a Senior AI Engineer at Knotch, you will develop AI agents for workflow automation, design backend and frontend services, and collaborate with teams to integrate AI into products. Your role includes optimizing systems for performance and ensuring agent safety and governance.

Lead architecture and delivery of agentic AI infrastructure: multi-agent orchestration, real-time conversational reasoning, retrieval/memory systems, LLM optimization, safety/observability, and secure tool integration. Mentor senior engineers and collaborate cross-functionally to build production-grade autonomous agents for enterprise workflows.

As a Lead Data Engineer, you'll design and implement AI-powered data systems, focusing on natural language queries and scalable frameworks. Collaborate with teams to optimize data access and enhance reporting tools.

In this role, you will lead AI personalization initiatives, develop AI/ML models for user experience, collaborate across teams, and ensure rigorous development practices.

The Staff AI Engineer will design and deploy production-level AI systems, guiding architectural decisions and collaborating with teams to build AI features at scale.

As an Applied AI Engineer, you'll build AI agents and experiences from concept to production, collaborating across teams and optimizing systems for usability and quality.