Top Tech Jobs & Startup Jobs in Los Angeles, CA

Lead complex data engineering engagements, manage stakeholders and risks, coordinate offshore teams, and build scalable Azure data pipelines. Develop ingestion and transformation solutions using Azure Databricks, Data Factory, Spark, Delta Lake, SQL, and Python. Harmonize raw data into consumer-ready formats, query large datasets, support on-premises cloud migration, and collaborate with executives and delivery teams.

Manage enterprise BI consulting initiatives by gathering stakeholder requirements, designing data models and flows, communicating architecture, and overseeing Power BI dashboard delivery. Lead design reviews, data validation, governance, risk mitigation, compliance, issue resolution, and offshore collaboration. The role requires strong stakeholder management, enterprise reporting experience, and expertise with Power BI, with Alteryx and Tableau preferred.

Lead the design of data architectures in Multi-Cloud environments, oversee migration of legacy systems, develop predictive models, and mentor technical teams.

The Alteryx Lead Consultant will analyze business requirements, design data flow processes, and support the migration of Alteryx workflows to tools like Snowflake and Power BI while focusing on cost reduction and performance optimization.

Designs and prototypes scalable agentic AI architectures across Azure, AWS, or GCP. Responsibilities include multi-agent orchestration, LLM applications, RAG pipelines, memory and vector search, enterprise integrations, cloud-native engineering, code reviews, AI governance, security guardrails, and stakeholder leadership. The role requires hands-on development, framework evaluation, and translating business needs into production-ready AI platforms.

Deploys, integrates, and scales enterprise Generative AI solutions across Azure environments. The role develops LangGraph agentic workflows, fine-tunes and evaluates LLMs, reduces hallucinations, integrates retrieval systems and APIs, and collaborates with customer engineering teams. Responsibilities also include requirements documentation, process mapping, automation engineering, software architecture, and communicating business value.

Lead hands-on architecture, development, deployment, and optimization of enterprise GenAI, RAG, Agentic AI, and Neo4j Knowledge Graph solutions. Build data pipelines, APIs, microservices, and cloud-native AI infrastructure; rapidly deliver customer POCs and production systems. Serve as the primary technical interface for enterprise clients, troubleshooting performance, scalability, reliability, and cost issues while providing technical consulting.

Deploys, integrates, and scales enterprise generative AI solutions in customer cloud environments. Responsibilities include architecting GCP and Vertex AI infrastructure, deploying and optimizing LLMs, building RAG data and vector search pipelines, managing GPU/TPU workloads on GKE, automating infrastructure with Terraform, and advising clients on AI safety, prompt engineering, hallucinations, and inference costs. The role also collaborates with research and platform teams and requires travel to client sites.

The Databricks Architect will design and implement large-scale data solutions, optimizing performance and reliability, while leading initiatives in data engineering.

The Machine Learning Engineer will develop software solutions, optimize data pipelines, and deploy machine learning models using cloud platforms and best practices.