Top Tech Jobs & Startup Jobs in Los Angeles, CA

Support employee experience, engagement, recruitment coordination, onboarding, offboarding, HR operations, employee lifecycle activities, reporting, and HR projects. Serve as a day-to-day employee contact, partner with hiring managers, manage documentation and communications, identify process gaps, and contribute to culture-building for a remote-first organization.

Build and own production AI-powered products across the frontend, backend, data, and cloud stack. Design multi-agent systems and RAG pipelines, orchestrate AI workflows, and deploy reliable, scalable features. Responsibilities include model serving, latency and cost optimization, prompt engineering, model evaluation, cloud infrastructure, and end-to-end product development using React, Node.js, PostgreSQL, and major cloud platforms.

Own full-cycle recruiting for niche senior engineering roles, including AI/ML, full-stack, .NET, DevOps, and architecture positions. Build outbound candidate pipelines using LinkedIn Recruiter, GitHub, Naukri, and Wellfound; conduct structured screening calls; and partner directly with the founder and engineering leadership. The role emphasizes advanced Boolean and X-ray sourcing, technical resume evaluation, meaningful candidate conversations, and high-quality shortlists.

Architect and deliver production enterprise AI systems, including multi-agent and RAG pipelines and full-stack applications. Build solutions using Python, TypeScript, Next.js, Node.js, FastAPI, Kubernetes, and cloud platforms. Lead client discovery workshops, proposals, proofs of concept, and C-level presentations while translating business needs into scalable AI implementations. Requires strong engineering experience, hands-on GenAI and LLM delivery, full-stack fluency, and U.S. enterprise consulting experience.

Build and own production-ready AI-powered features across frontend, backend, infrastructure, and deployment. Collaborate with product teams to turn ideas into scalable solutions, design LLM workflows, orchestrate multiple AI models, and optimize latency, cost, and performance. The role also establishes AI-assisted engineering practices and contributes to usability, product quality, architecture, and business outcomes.