Top AI Engineer Jobs in Los Angeles, CA

Build production-ready intelligent automations and agentic AI solutions. Full-stack development using TypeScript or Python, LangChain, vector DBs, RAG, and tool-calling. Collaborate with clients, ensure maintainable, tested, scalable deployments, CI/CD, observability, and model fine-tuning or deployment.

The Principal AI Engineer leads implementation work in the AI Innovation Lab, focusing on building technical infrastructure, developing AI prototypes, and establishing best practices in a cloud environment.

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.

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.

Design and prototype LLM- and agent-based workflows (RAG, tool-calling), build reusable connectors and agent templates, integrate data science models, define clean API boundaries, implement lightweight evaluation/logging, and collaborate with data science and leadership to operationalize AI systems.

The role involves researching, developing, and implementing AI solutions, optimizing models, integrating AI into workflows, and collaborating with teams to enhance business efficiency.

Client-facing AI engineer who develops and deploys generative AI/LLM solutions, collaborates with data scientists and engineers, leads cross-functional projects, and delivers technical solutions and presentations to clients.

The Senior Gen AI Engineer will design AI agents, build knowledge graphs, implement retrieval-augmented pipelines, and integrate data sources to enhance AI systems.

The ML/AI Engineer will develop and deploy machine learning models, design data pipelines, support AI tools, and build digital twins, collaborating with cross-functional teams.

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.

Design, develop, and deploy AI/ML solutions—especially generative and agentic AI—build LLM and RAG architectures, implement MLOps pipelines, prototype PoCs, and integrate models into production using cloud, containerization, and CI/CD practices while collaborating across teams.

Design and build autonomous, enterprise-grounded AI agents and workflows using the Elastic Stack, RAG, and LLMs. Integrate models with internal APIs and SaaS, manage deployment and scaling on cloud/Kubernetes, ensure security/compliance, document systems, and provide technical leadership for agent lifecycle and performance optimization.

The AI Engineer will develop AI-driven marketing tools, building APIs, data pipelines, and collaborating with teams to innovate. Requires experience in software development and generative AI concepts.

The Senior AI Engineer will design and deploy AI-driven marketing solutions, lead R&D efforts, and collaborate with stakeholders to translate business needs into scalable applications.

The AI Engineer II will develop and deploy machine learning solutions in healthcare, mentor junior staff, and work on complex data analytics to improve patient care and operational efficiencies.

The Staff AI Engineer will architect and deliver AI systems, mentor engineers, and design scalable infrastructure for LLM-driven applications.

The Senior AI Engineer designs and deploys AI agents and workflows, collaborating across teams to deliver reliable AI solutions that drive business outcomes.

The Full Stack AI Engineer will develop and maintain AI agents, build clinician-facing products using React and Python frameworks, and manage data infrastructure to support clinical workflows.

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.

The Senior Applied AI Engineer will drive AI innovation, design pilots, enhance AI patterns, develop architectures in AWS, and communicate results effectively.

The Principal AI Engineer will design and execute AI infrastructure, mentor teams, and architect systems for improved workflows and API integration at VideoAmp.

The role involves integrating AI models into existing products, collaborating with the data science team, and enhancing user experiences. Responsibilities include model evaluation, framework design, and monitoring AI performance.

The AI Engineer will design backend systems for workflows, optimize multi-agent pipelines, develop knowledge retrieval systems, and collaborate to integrate workflows using LLMs and traditional systems.

The Applied AI Engineer role involves designing, building, and deploying AI-powered systems, collaborating with business teams, and measuring solution impact. Responsibilities include translating workflows into systems, driving outcomes, and ensuring regulatory compliance while fostering community sharing of learnings and tools.

The AI Engineer III is responsible for the reliability and scalability of AI solutions, managing CI/CD pipelines, observability, and ensuring security in deployments. They architect and maintain tools within Azure AI Foundry, collaborate with SRE teams, and optimize model performance while enforcing governance through automated controls.