Top AI Automation Jobs in Los Angeles, CA

Lead the design and implementation of AI agents and automation across pro-code and no-code platforms. Define repeatable automation patterns, integrate AI platforms with business tools via APIs, build RAG pipelines and vector DB integrations, write Python scripts for complex integrations, and guide technical decisions while working closely with the VP of AI to review agent performance and scale solutions.

The Director of AI Automation leads AI-driven automation systems, translating strategic goals into practical solutions, managing teams, and enhancing operational efficiency.

As a Senior Software Engineer, design and develop automation solutions leveraging AI, integrate AI-driven components, and maintain backend systems while collaborating cross-functionally to improve workflows.

Join a talent pool to teach, author, or advise on AI-powered automation. Deliver live workshops, create course materials, design exercises, shape curriculum, review technical content, and support program updates. Part-time (10–15 hrs/week), remote with collaboration in European time zones. Roles span junior to senior levels and emphasize hands-on experience with automation platforms and real-world operational workflows.

Build and own an internal AI-powered recruiting pipeline: end-to-end LLM-based sourcing, screening, AI interviews, evaluation logic, and deep integrations with ATS and scheduling to automate hiring workflows.

The AI Automation Engineer develops AI-driven systems to automate sales and marketing workflows, partnering with various teams to enhance revenue generation and process efficiency.

Design and implement AI-native workflow orchestration and automation systems for legal services. Build integrations between AI models, CRMs, document systems, client portals, and internal tools. Develop agent workflows, vector retrieval and observability pipelines, monitor reliability and performance, troubleshoot integrations, and support governance, compliance, and scalable client experiences.

Lead design and execution of test strategies for generative AI systems (LLMs, RAG, agents). Validate accuracy, factuality, fairness, bias, consistency, and security of AI outputs. Create API and model-endpoint tests, automate test suites, perform adversarial and exploratory testing, detect hallucinations, validate data quality and performance metrics, and collaborate with cross-functional Agile/DevOps teams to ensure safe, reliable GenAI deployments.

Lead AI-native technical program delivery for the ADVEV platform: translate roadmaps into execution, build prototypes and AI automation, coordinate product and engineering stakeholders, drive release planning, and implement dashboards and agentic tooling to automate program operations and reporting.

The role involves designing and implementing automation systems, improving workflows, and developing tools for sales support using AI and automation platforms.

As a Staff AI Engineer, you will design and implement AI-powered automation for internal departments, manage the full project lifecycle, and enhance various processes across CargoSprint, focusing on business impact and collaboration.

Design and build AI- and automation-driven solutions to accelerate Mortgage Cadence Platform configuration using LLMs and workflow automation. Develop integrations with system APIs, partner with implementation teams, create documentation and training, and propose new tools to improve implementation accuracy and scale.

Design and deliver AI-powered analytics, dashboards, and decision-support tools for commercial healthcare teams. Build LLM-based agents, use cloud data platforms (Azure/AWS/Snowflake), ensure data governance and compliance, translate complex healthcare data into executive-ready insights, and automate insight generation to support growth and operations.

Lead and grow an engineering team to design and deliver AI-driven, spec-based automation for media workflows (MAM, ingest, transcoding, streaming, broadcast). Own AI roadmap, integrate LLMs/agents into production, improve CI/CD and developer tooling, enforce security best practices, and partner with product and operations to scale autonomous media automation systems.

Develop and manage intelligent automation solutions using UiPath, bridging communication between project managers and clients, conducting process analysis, and providing documentation.

Design and execute test strategies and automation for cloud-native and GenAI/AI-ML systems. Perform functional, integration, performance, security, and API testing; validate model accuracy, fairness, robustness, and data quality; integrate automation into CI/CD; track defects; mentor junior QA engineers.

Lead enterprise adoption of Microsoft Copilot, Copilot Studio, and Power Platform by analyzing business processes, designing AI agents, building ROI-backed automation roadmaps, delivering training and prompt engineering best practices, and measuring utilization and productivity improvements across functions.

Lead development and execution of MVB's AI and automation strategy, including Generative and Agentic AI and RPA. Partner with business and technical stakeholders to design, pilot, and scale solutions, establish governance and best practices, monitor performance metrics, manage vendors, and deliver training to ensure ethical, secure, and effective AI deployments.

Build AI-powered workflows, agents, and integrations to automate marketing research, creative asset preparation, campaign analysis, reporting, and internal coordination. Prototype and productionize LLM-based tools, connect data sources and ad platforms, validate automation quality with real use cases, and document systems for reuse and scaling.

Build and maintain internal and customer-facing web/cloud apps and AI automations. Integrate with third-party APIs (QuickBooks, Microsoft Graph, Zoho, Zoom), implement generative-AI features, ensure security, deploy to cloud, and collaborate with leadership and IT. Work independently on design, testing, and maintenance across varied projects.

Build and ship AI-driven automation across the go-to-market lifecycle: prospecting, lead routing, deal support, retention, and instrumentation. Design agents and workflows, connect GTM systems and data, deploy and monitor production AI, set guardrails and evals, and partner with Sales, Solutions Architecture, Marketing, and RevOps to measure and improve impact.

Lead design and delivery of agentic AI systems and LLMOps on AWS to generate, validate, and deploy infrastructure-as-code (Terraform). Build multi-agent applications, RAG pipelines, and AIOps for cloud operations; integrate AI into CI/CD and ITSM. Set technical direction, establish guardrails/policy-as-code, curate reusable Terraform modules, and mentor engineering teams.

Design and build automation frameworks and evaluation pipelines for agentic AI products. Develop non-deterministic tests, golden datasets, tool-use validation, prompt regression tests, latency/token monitoring, hallucination detection, and collaborate with AI engineers to convert requirements into measurable automated test cases.

Lead QA Automation for agentic AI products by designing eval pipelines, golden datasets, and automated tests for tool-use, hallucination detection, latency/token monitoring, and regression across models and prompts. Integrate performance testing into CI/CD and collaborate with AI engineers to convert requirements into measurable automated evaluations.

Design, build, test, and deploy AI agents, agentic workflows, and automation solutions. Partner with stakeholders to prototype and productionize full-stack AI applications across cloud, VPS, and local GPU environments while ensuring scalability, security, and performance.