Top Tech Jobs & Startup Jobs in Los Angeles, CA

Full-cycle enterprise sales role responsible for prospecting, developing, qualifying, and closing deals with large, multi-stakeholder organizations. The position sells FacilitiesLink, a facilities information platform for planning, building, and operating large-scale campus environments. Compensation includes 50% commission, a $20-per-hour guaranteed draw, and on-target earnings starting at $150,000 annually. Flexible work arrangements are available, with occasional travel required.

Leads and scales the implementation team, manages and mentors implementation specialists, optimizes deployment playbooks, oversees implementation risk and quality, handles executive escalations, and partners with Sales, Product, Engineering, and Client Success. Tracks implementation KPIs, resource utilization, backlogs, and CRM data integrity while driving faster customer time-to-value, retention, and account growth.

Design and deploy production AI assistants, copilots, agents, RAG systems, and workflow automation using enterprise data. Build AI backend services, APIs, microservices, and AWS serverless workflows; integrate enterprise platforms; implement observability, responsible AI, human-in-the-loop controls, and traceability. Partner with Data, IT, and business teams to improve operational processes and decision-making while managing production incidents, model rollbacks, performance, accuracy, and cost.

Conduct full-lifecycle recruiting for technical and engineering roles, emphasizing creative sourcing of senior talent. Partner with hiring managers to define requirements and interview processes, improve recruiting workflows, manage multiple candidate pipelines, and deliver an excellent candidate experience. The role requires recruiting experience in technology startups and defense or adjacent industries, along with strong sourcing and process-management skills.

Owns executive relationships and revenue growth for 2–4 high-value enterprise accounts. Develops multi-year account plans, expands product adoption, identifies cross-sell and upsell opportunities, leads renewals and contract negotiations, and coordinates Product, Marketing, Client Success, and Solutions teams. The role also conducts strategic business reviews, represents the company with senior stakeholders, and drives profitable long-term partnerships across Roadside Assistance and Accident Management offerings.

Lead technical strategy and execution for multi-quarter initiatives, build and maintain software systems using AI, mentor and elevate engineers, collaborate across disciplines, and protect user privacy and security. The role involves working in an AWS and Kubernetes environment with technologies including Python, TypeScript, React, Go, Airflow, dbt, and Claude Code.

Build and maintain Customer Success and Implementation playbooks, SOPs, training programs, knowledge bases, presentation materials, and scalable workflows. Partner cross-functionally to communicate process and product changes, improve automation and efficiency, identify customer risks, and measure enablement effectiveness. Support implementation, launch readiness, customer health, escalations, business reviews, renewals, and expansion.

Build and ship production AI systems across retrieval, knowledge graphs, inference, agentic workflows, and data platforms. Develop customer-context retrieval, scored signals, evaluation and observability capabilities, and workflows that turn insights into action. Work hands-on with large and small models, durable orchestration, cloud deployment, inference-cost optimization, and high-volume observability data. Establish reusable engineering patterns, collaborate with product and platform teams, and mentor through strong technical contributions.

Administers and analyzes sales compensation programs, including commission payout processing, data auditing, dispute resolution, plan modeling, reporting, and dashboard maintenance. Partners with sales, finance, and HR teams to ensure accurate payouts, compliance, documentation, and process improvements. Requires strong Excel modeling skills, CRM and incentive compensation platform experience, analytical ability, communication skills, and independent judgment.

Design, build, and operate high-throughput, low-latency ad-serving infrastructure processing millions of requests per second. Optimize GPU-powered TensorRT inference, feature stores, model serving, benchmarking, experimentation tooling, and system reliability. Partner with machine learning engineers to productionize models and own systems through design, deployment, observability, capacity planning, incident response, and optimization.