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# Senior Software Engineer, Data & AI

- **Company:** LIGHTSPARK LLC
- **Location:** Culver City, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Sql Data Warehouse, Artificial Intelligence, BigQuery, Encodings, Information Engineering, Data Infrastructure, Data Integrity, Python (Programming Language), Machine Learning, Node.Js, Blockchain, Software Engineering, TypeScript, Workflow Management Systems, Large Language Models, Snowflake, Prompt Engineering, Backend, Agentic-AI, Usage Tracking, AI Platforms, Machine Learning Operations, Databricks
- **Published:** October 26, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-software-engineer-data-ai-culver-city-ca--6b6a0834-2913-4258-a9bd-3898e273d4a7

## About the Role

Software Engineering, Artificial Intelligence (AI), Digitial Currency, Systems Maintenance, Artificial Intelligence (AI) Agents, Software Engineering, Artificial Intelligence (AI), Sales, Electrical Wiring, Legal, * 4+ years experience shipping and maintaining production systems; data engineering, ML engineering, and backend/full-stack backgrounds all fit

 * You've built an internal platform or workflow system that other teams adopted, not just features on top of one
 * You've built with LLM APIs, agent frameworks, and MCP in production, beyond prompting, and you know what belongs in code versus a model
 * Strong fundamentals in TypeScript/Node or Python and the willingness to work in both, plus fluency with a cloud data warehouse such as BigQuery, Snowflake, or Databricks
 * You can sit with a non-technical team, understand how their work actually happens, and come back with a system
 * Comfortable working with ambiguity in a startup environment
 * Experience in payments, crypto, or blockchain is a plus, but not required
 * Based in LA or Openness to relocate to Los Angeles, California

This is not an ML infrastructure, model-training, or prompt-engineering role. You might currently be an AI engineer, ML engineer, data engineer, or full-stack engineer who has spent the last year or two building agents and internal tooling. If you don't match every line above but have built systems like these, we'd like to hear from you.

## Description

* Building and owning our internal AI platform: the agent harness, MCP servers and tool integrations, context and access services, sandboxed execution, and cost and usage tracking
 * Embedding with Finance, Sales Ops, Compliance, and onboarding to understand how their work actually happens, then shipping the systems that replace the manual version and handing them off to those teams
 * Extending our data infrastructure alongside our Staff Data Engineer: DBT models, BigQuery, orchestration, and the production pipelines
 * Sharing ownership of monitoring, alerting, and data reliability for the systems that unblock product launches
 * Partnering with Engineering to optimize their own dev systems and tooling