Top AI Jobs in Los Angeles, CA

Principal AI Architect responsible for defining and governing enterprise Generative AI and AI/ML architectures. Designs LLM, RAG, vector database, MCP, multi-agent, and orchestration solutions; establishes reusable patterns, security, governance, and responsible AI standards; leads architecture workshops; partners with product, business, data, platform, and application teams; and provides technical direction for scalable, secure, production-ready AI capabilities.

Design, build, deploy, and operate production AI-native systems spanning applications, APIs, data, cloud infrastructure, DevSecOps, security, observability, and agentic AI. Lead architecture, client engagements, multidisciplinary engineering teams, and technical delivery from ambiguous requirements through production. Build cloud-native platforms, CI/CD pipelines, secure data and context architectures, AI integrations, agent orchestration, evaluations, and production safeguards. Establish reusable engineering standards, tooling, and practices for enterprise AI adoption.

Define enterprise AI architecture and governance; build secure LLM platforms, gateways, agent frameworks, retrieval systems, access controls, and cost tracking. Establish AI integration across software development and CI/CD, including automated testing and policy gates. Design secure data boundaries for CUI and ITAR data across cloud, government, on-premises, and air-gapped environments. Align AI usage with CMMC, NIST, FedRAMP, ITAR/EAR, and AI risk-management standards.

Leads Riot’s AI Foundations engineering organization, setting technical strategy, roadmap, architecture, and investment priorities. Oversees engineering managers and multiple teams, develops organizational capabilities, drives hiring and performance management, and ensures reliable, secure, scalable AI/ML and software systems. Partners with product, game, platform, data, research, and executive leaders while advancing responsible AI, operational excellence, technical quality, and reusable AI platform capabilities across Riot.

Lead the strategy, architecture, deployment, and operation of League of Legends’ AI/ML platforms at global scale. Establish MLOps, serving, feature platform, governance, security, observability, incident response, and cost optimization standards. Drive implementation across multiple products, improve ML developer experience, mentor senior engineers, coach cross-functional teams, and influence recruiting and product strategy.

Own and improve ClickUp’s voice AI systems, including real-time speech-to-text, audio processing, context-aware transcription, LLM post-processing, mention resolution, formatting, and voice-to-action workflows. Evaluate and integrate ASR models for accuracy, latency, and cost, while collaborating across product and platform teams to deliver voice and multimodal assistant features across desktop, mobile, web, and browser extension products.

Design, develop, and implement AI/ML models; analyze large datasets; integrate AI solutions into existing systems; apply MavLink for autonomous systems; collaborate across teams and improve ML development processes.

Build and deploy AI-powered tools for Rula’s business and clinical teams by observing workflows, rapidly delivering production software, measuring usage and impact, and enabling teams to operate tools independently. The role requires privacy-by-design practices, rigorous AI evaluation, customer-centric discovery, and integration with complex legacy systems. Staff engineers may optimize LLM costs and quality while creating reusable building blocks for future teams.

The Staff AI Engineer will analyze AI quality, implement improvements, manage projects, collaborate with teams, and shape AI capabilities in a remote-first environment.

Own and ship backend systems and agentic AI features for telemetry analysis: design agent tool interfaces, build distributed job execution on Kubernetes, implement APIs and MCP server, integrate frontier models, and build evaluation and observability for production agent workloads.

Supports AI-driven workflow discovery, redesign, solution prototyping, requirements development, testing, rollout, and adoption. Bridges specialty experts, product managers, engineers, and transformation leaders while translating redesigned workflows into standardized services, deliverables, staffing models, pricing frameworks, and commercial offerings. The role combines generative AI, product development, business transformation, service design, and commercial modeling to improve how Edelman delivers and markets its services.

SynX Therapeutics, a biotech start-up, invites speculative applications for future roles related to drug discovery and engineered biology.

Leads the design, development, and deployment of scalable AI, generative AI, and machine learning solutions. Oversees data infrastructure, integration, data quality, and advanced analytics while managing client engagements and executive relationships. Drives business development, strategic direction, innovation, and AI-driven automation. Mentors teams, develops future leaders, and fosters collaboration, integrity, and client satisfaction across complex projects.

Own the design, roadmap, security, observability, and production operations of Tinder’s internal AI agent platform. Build gateways, MCP connectors, identity and delegation systems, fine-grained authorization, guardrails, audit trails, evaluation workflows, cost attribution, and reliable runtime infrastructure. Partner with Security and internal engineering teams, lead incident response and on-call operations, establish connector standards, and mentor engineers building on the platform.

Own and deploy statistical, AI, and machine learning models for demand forecasting, inventory optimization, and Sales, Inventory, and Operations Planning. Analyze forecast accuracy, develop scenarios, manage data pipelines, create KPI reporting, and translate insights into operational recommendations. Partner cross-functionally with Sales, Marketing, Engineering, Purchasing, Production, Finance, and business units to support rolling 12–24-month planning and continuous process improvement.

Manage the Dev AI engineering team building AI infrastructure, developer tooling, agentic coding tools, workflow platforms, SDKs, and AI-assisted migration systems. Shape technical strategy, partner with senior engineering leaders, evaluate emerging AI technologies, consult with internal teams, build stakeholder relationships, and coach distributed engineers. The role emphasizes developer productivity, cross-functional collaboration, rapid experimentation, and measurable impact across Airbnb.

Designs and builds large-scale clinical, claims, and document data platforms on Google Cloud. Leads architecture, production engineering, AI-assisted development and operations, including agent guardrails, observability, automation, auditability, and regulated-environment controls. Develops AI and machine learning systems involving retrieval, extraction, evaluation, and serving. Partners across engineering, security, privacy, compliance, and governance teams while communicating technical strategies to executives and customers.

Support and scale cloud, DevOps, and production ML infrastructure. Responsibilities include managing AWS, Databricks, SageMaker, Kubernetes, CI/CD pipelines, Infrastructure as Code, model serving, monitoring, security, observability, incident response, and disaster recovery. The role automates deployments and operational processes, improves reliability, supports AI and agentic products, and collaborates with software, ML, QA, security, and support teams.

Build and deploy production AI, generative AI, machine learning, data engineering, and advanced analytics solutions for a regulated bank. Develop Snowflake-centered pipelines and Azure integrations, implement LLM, RAG, agent, and automation capabilities, and establish testing, monitoring, documentation, governance, security, and responsible AI practices. Partner with business, technology, risk, compliance, and legal teams to identify valuable use cases, evaluate emerging technologies, and scale reliable AI capabilities.

Design, implement, and train reinforcement learning and multi-agent algorithms; build scalable Python-based training pipelines and simulated environments; run distributed training with cloud and container orchestration; transition models to production, optimize system performance, and collaborate with domain experts to align rewards and evaluations with mission objectives.

Lead the technical direction, architecture, and development of Compass, an LLM-powered agent platform. Design multi-agent systems, MCP and A2A integrations, orchestration, evaluation, and observability infrastructure. Drive cross-team technical projects, production support, engineering quality, mentoring, and adoption of AI-assisted development practices. Partner with Product, QA, Design, Operations, and Engineering stakeholders to deliver reliable agentic systems.

Build AI-powered tools that accelerate nuclear engineering workflows, including safety and physics analyses, neutronics simulations, and automated ticket, design-tree, and file-management processes. The role embeds with engineering teams to identify bottlenecks, prototype solutions, and deploy production-grade Python tools using LLMs, AI agents, RAG, and tool-use architectures. Work is fully onsite, may require extended hours, and requires US citizenship with the ability to obtain and maintain a Q clearance.

Lead the AI Platform team in building reliable, secure, observable infrastructure, shared services, deployment patterns, and operational practices for AI capabilities. Set technical priorities, coordinate cross-team dependencies, guide architecture and production operations, improve developer experience, and coach engineers while contributing to complex technical work.

Advise executives and technology leaders on AI transformation for contact center and customer service operations. Assess environments, identify AI opportunities, develop roadmaps and business cases, lead executive workshops, define use cases involving virtual agents and copilots, and guide implementation with clients, vendors, and delivery teams. The role requires extensive contact center, consulting, customer experience, CCaaS, and AI initiative leadership experience.

Lead strategy, roadmap, and scaling of enterprise AI/ML platforms (including GenAI and agent frameworks). Enable cross-functional teams to build, deploy, govern, and operate production-grade AI solutions; define architecture and guardrails; track adoption, reliability, cost, and developer productivity; partner with Security, Privacy, Cloud, and vendor partners; and drive platform delivery through agile execution.