Top Tech Jobs & Startup Jobs in Los Angeles, CA

Owns end-to-end delivery of generative AI solutions, including LLMs, RAG, and AI agents, for BFSI applications. Translates business needs into AI product roadmaps and technical requirements, coordinates business, data science, and engineering teams, and leads AWS deployments. Defines success metrics and monitors model performance, adoption, governance, compliance, and business outcomes while staying current with agentic AI and enterprise AI platforms.

Develop and maintain demand forecasts across products, markets, customers, and channels. Analyze sales, inventory, promotions, seasonality, and market trends; investigate forecast performance and root causes; support product launches, lifecycle planning, and S&OP. Create reports and dashboards using Excel, SQL, Power BI, or Tableau, maintain planning data in ERP/MRP systems, and collaborate with Sales, Marketing, Supply Planning, Finance, and Analytics teams.

Develop and maintain Power BI dashboards, reports, data models, KPIs, and executive scorecards using SQL and healthcare claims data. Analyze trends, anomalies, savings opportunities, compliance risks, and Payment Integrity performance. Partner with business, compliance, clinical, and technology stakeholders to translate requirements into scalable regulatory and operational analytics solutions. Ensure data quality, governance, and reporting consistency while supporting forecasting, root cause analysis, and AI-enabled analytics initiatives.

Leads client architecture and delivery for large-scale Google Cloud data engineering, data warehousing, analytics, and AI/ML platforms. Defines technology strategy, designs GCP-native solutions, governs complex programs, resolves critical technical issues, and mentors engineering teams. Partners with executive stakeholders to translate business needs into scalable solutions while contributing to reference architectures and technical enablement. Requires deep GCP, BigQuery, Vertex AI, data engineering, cloud architecture, and client-facing delivery expertise.

Build production-grade LLM applications (agentic chatbots, semantic search, RAG systems), fine-tune foundation models, implement RAG and agent architectures, integrate AI assistants with systems, design evaluation/governance pipelines, collaborate with cross-functional teams, and mentor junior data scientists.

Design, build, and operate large-scale data platforms and production ETL/ELT pipelines. Partner with data science, analytics, and business teams; manage cross-functional delivery, QA, observability, data quality, experimentation infrastructure, and statistical model validation. Deploy containerized workloads through Docker, Kubernetes, CI/CD, and Helm. Own data operations, monitoring, incident response, SLAs, runbooks, and pipeline reliability while delivering accurate, scalable, and cost-efficient data assets.

The Senior Data Modeler is responsible for designing and managing data models, ensuring data accuracy, compliance, and alignment with business needs.

Lead supply chain analytics engagements: manage client teams, design data-driven solutions for demand forecasting, inventory and network optimization, drive key initiatives to closure, and provide thought leadership in supply chain analytics.

The Engagement Manager will lead analytics and AI-driven programs, manage client relationships, build high-performing teams, and innovate solutions using decision science and data science.

Lead go-to-market and revenue for the Cogentiq Invoice-to-Cash product: drive new business, manage full sales lifecycle, design commercial models, collaborate cross-functionally, and secure enterprise deals while supporting onboarding and growth.