Top AI Automation Jobs in Los Angeles, CA

Build end-to-end internal AI agents and workflow automations: discover high-value opportunities, redesign processes, implement LLM-based agents with integrations, deploy and operate solutions, and ensure security, compliance, monitoring, and adoption across GTM teams.

Enable and mentor partners to sell and deliver NiCE AI/CCaaS solutions. Lead technical discovery, demos, PoVs, and architecture reviews; build partner enablement content; manage technical partner relationships, integrations, release impacts, and service scoping.

The Principal Consultant leads AI and digital transformation engagements, guides clients in identifying AI opportunities, builds strategies and roadmaps, implements solutions, and develops teams to achieve measurable business outcomes.

The role leads AI adoption across business functions, prioritizing use cases, building business cases, and driving organizational change necessary for successful implementation. It requires collaboration with IT leadership and the presentation of ROI to business stakeholders.

Hands-on technical leader who designs, builds, and deploys production-grade AI automation and agentic workflows. Responsibilities include rapid prototyping, RAG and document-intelligence systems, API integrations, orchestration, monitoring, reusable AI assets, and mentoring a small engineering team to deliver frequent releases and measurable business impact.

Own and administer Salesforce and NetSuite while designing and deploying production-grade AI-driven automations and agent workflows. Ensure data governance, PHI/HIPAA compliance, release management, and quote-to-cash integrity. Partner cross-functionally to prioritize work, coach teams, document systems, and measure impact of automation on operations and revenue.

Build and ship AI-native systems for a fintech app: AI agents, RAG/retrieval systems, tool-calling and automation for onboarding, KYC, support, risk, CRM and operations. Work with product and engineering to design reliable, low-hallucination, cost- and latency-aware solutions and turn manual processes into scalable AI-enabled systems.

The SME will develop a curriculum on AI for finance, creating engaging content and videos to train finance professionals in AI applications. They must leverage their extensive finance experience and AI understanding to enhance learner success.

The AI Automation Engineer will automate internal processes, mentor non-technical staff on building tools, and ensure solutions deliver measurable business impact using AI technologies.

The AI Automation Intern will design and deploy AI-powered automations, prototype AI tools, evaluate models, and build dashboards within a private equity context.

Build and deploy production micro-apps and LLM-powered agents on a governed GCP platform. Integrate AI with systems (Salesforce, Slack, NetSuite, SQL), harden apps with auth, secrets, CI/CD, logging and monitoring, automate maintenance, and implement evaluation and observability for model quality and drift.

Contribute to building and hardening micro-apps and AI integrations on a shared GCP platform. Complete bug fixes and small features, participate in code and design reviews, apply security and software development best practices, monitor applications and follow runbooks, and use AI tools to assist development, testing, and documentation while learning from senior engineers.

Design and deliver LLM-powered, agentic AI systems to automate customer support and compliance. Build scalable, secure backend infrastructure in Python and Go, integrate third-party models/APIs, implement grounding and guardrails, and measure performance. Lead end-to-end projects, mentor engineers, conduct code reviews, and participate in on-call and incident response to improve resolution times and reduce operational costs.

Lead intake, roadmap, and governance for an AI automation/platform team. Harden and ship business-built AI apps to production with secure GCP platforms, define acceptance criteria and responsible-AI gates, manage vendor buy-vs-build decisions, drive adoption, measure outcomes, and manage AI economics and stakeholder communication.

Support AI project teams by executing workstreams, preparing client-facing presentations and documentation, assisting implementation activities, maintaining required certifications, using relevant technology, communicating with stakeholders, and traveling as needed for client engagements.

Build end-to-end AI-driven automations across finance, operations, and clinical-support: browser automation for invoices, document data extraction, internal AI agents, data integrations, and fast prototypes. Work directly with the CAIO to turn loose specs into shipped tools.

The AI Automation Intern will design and deploy AI automations, build tools, evaluate AI models, and create dashboards while working directly with the founding partner.

Lead client engagements in insurance data, analytics, and AI: define roadmaps, run discovery sessions, design solutions, manage delivery and teams, develop proposals, and ensure DataOps, cloud (AWS), governance, and best practices across AI and analytics initiatives.

Lead execution of Product Engineering AI and automation initiatives across photonics products. Build and deploy reusable AI/automation tools, transform engineering data into AI-ready systems, and drive cross-functional adoption to improve development, qualification, manufacturing, and reliability processes.

Design and build AI-powered automation workflows and integrations for Pragmatico and clients. Lead discovery, architect solutions using LLM APIs and integration platforms (Zapier/Make.com), present solutions to stakeholders, train client teams, and create reusable automation frameworks and thought leadership content.

Design, build, and scale AI-powered automation using LLMs, RAG, vector DBs, prompt pipelines, and agent systems. Integrate with internal tools and cloud platforms, implement orchestration, observability, security guardrails, measure impact, and partner cross-functionally to replace manual processes with reliable production-grade automation.

Lead AI-driven reconciliation and automation to improve encounter data quality. Own model performance, identify root causes, partner with technical and business teams to enhance models, prioritize roadmap, and scale automation while communicating results to stakeholders.

Designs, builds, tests, and deploys AI-enabled automations and copilots for GTM and RevOps. Creates reusable agent templates, prompt libraries, and orchestration patterns; implements end-to-end API integrations; monitors performance; documents and hands off production solutions; and trains/coaches business teams on safe, responsible AI usage and prompting best practices.

Lead and build an enterprise AI and automation program: define operating model, roadmap, governance, and KPIs; prioritize and deliver AI/RPA use cases; partner with IT, business, compliance, and vendors; ensure responsible AI practices and regulatory alignment; drive adoption, change management, and team development.

The AI Automation Engineer will apply AI in finance operations to automate processes like AP, AR, and reconciliation, ensuring compliance and performance measurement.