Top Tech Jobs & Startup Jobs in Los Angeles, CA

The Staff AI Engineer will design and build AI Assistants that automate workflows, integrate enterprise tools, and ensure systems are production-grade and secure. Responsibilities include developing APIs, enhancing assistant quality, collaborating with teams, and evaluating new AI models and tools.

The Enterprise Account Executive is responsible for developing a sales strategy, generating leads, building relationships, and achieving sales targets in a high-growth organization.

As a Software & Data Engineer, you will design data pipelines, deploy AI tools, build data warehouses, and integrate systems for clients, ensuring data quality and performance.

The Account Manager will support publication accounts by managing client partnerships, project execution of manuscripts, and ensuring compliance with publication standards.

Account Executives at Emburse are responsible for managing the entire sales cycle, developing strategies to boost revenue, and building strong relationships with clients and partners. They must have significant experience in selling financial SaaS solutions.

Danti seeks candidates interested in general roles as they grow, focusing on data accessibility using advanced search technologies and tools.

The Solutions Engineer at SpryPoint is responsible for leading the technical sales process, creating tailored demos, and serving as a trusted advisor to utilities considering SaaS solutions for operational modernization.

The Outside Sales Account Executive will manage the full sales cycle, develop relationships with local businesses, and achieve sales targets through cold calling and territory prospecting.

As the Senior Product Manager for Financial Services, you will oversee the financial experience for sports organizers, managing product strategy, execution, and compliance with financial regulations.

Build and own the reporting and insight layer: write optimized Redshift queries, build dashboards, monitor model feedback signals, triage and prioritize investigations for data science, maintain ETL pipelines ingesting semi-structured data, and enable Customer Success with clear metrics and onboarding checks. Move into model validation and automation to scale analytic workflows.