AI Developer

Live Events•Newark, DE

1d•Hybrid

About The Position

At Live Events and Pyrotecnico, we create unforgettable live experiences. Our teams produce fireworks, special effects, drone light shows, lighting, audio, video, rigging, and full-scale event production for major concerts, festivals, sporting events, corporate gatherings, and community celebrations across the country. We deliver end-to-end production solutions that bring creative visions to life. From high-energy touring shows to large-scale special events, we combine precision, innovation, and technical expertise to make every moment extraordinary. If you're driven by the thrill of live production and want to work alongside the best in the business, you've come to the right place. The AI Developer builds, deploys, and maintains production AI agents, integrations, and data pipelines across the company's ERP, CRM, and cloud systems. This hands-on role requires strong Python, direct LLM API development, and Google Cloud Platform experience. The ideal candidate can independently take projects from concept through deployment and support, with a focus on shipping practical solutions quickly and delivering measurable business value. This role may be based at any Live Events or Pyrotecnico office. Final reporting location will be discussed during the interview and hiring process.

Requirements

Strong Python experience building and maintaining production applications and API integrations.
Hands-on experience with direct LLM APIs (Anthropic, OpenAI, Vertex AI) and building AI agents without orchestration frameworks.
Production Google Cloud Platform experience with Cloud Run, Cloud Functions, BigQuery, Cloud Storage, service accounts, and IAM.
Experience deploying through the GCP CLI, including gcloud builds submit and gcloud run deploy.
Strong REST API integration skills, including authentication, OAuth, pagination, webhooks, and rate limits.
Strong SQL skills; BigQuery experience preferred.
Experience building AI workflows with human-in-the-loop controls, approvals, and audit trails.
Demonstrated experience shipping and maintaining production systems used by real users.
Ability to independently scope, build, deploy, and support projects
Business-oriented, pragmatic approach focused on shipping useful solutions quickly.

Nice To Haves

NetSuite development experience with SuiteScript 2.x and SuiteQL.
MCP server development experience.
HubSpot API / CRM integration experience.
Looker Studio or similar BI/reporting experience.
Experience integrating ERP/CRM systems and working with finance, sales, inventory, or other business data.

Responsibilities

Design, build, and maintain production AI agents, prompt management, context handling, and orchestration using Python and direct LLM APIs (Anthropic, OpenAI, Vertex AI) without reliance on heavy frameworks.
Deploy and operate workloads on Google Cloud Platform (Cloud Run, Cloud Functions, BigQuery, Cloud Storage) using GCP CLI tools (gcloud builds submit, gcloud run deploy), service accounts, and secure IAM permissions.
Build robust REST API integrations (OAuth, webhooks, rate-limiting), optimize SQL/BigQuery workflows, and maintain reliable data pipelines across ERP, CRM, and cloud infrastructure.
Own the entire lifecycle of software solutions—from initial code commit through testing, deployment, monitoring, troubleshooting, and long-term maintenance.
Work with business data (finance, sales, inventory, operations) to translate broad operational challenges and business goals into practical, codable AI and automation solutions.
Apply sound engineering judgment to balance architecture with speed to market, shipping high-impact, practical tools quickly while avoiding unnecessary complexity.
Design workflows that integrate seamlessly with real-world operations, including approval steps, escalation paths, and audit trails to ensure safe and valuable AI deployment.
Collaborate directly with business stakeholders and leadership across departments to scope projects, uncover automation opportunities, and clearly communicate the impact and trade-offs of technical decisions.
Partner closely with internal IT, operations, and business units to ensure AI agents and data integrations seamlessly align with existing systems and user workflows.
Clearly document code, API specs, deployment procedures, and operational guidelines so non-technical stakeholders and peer team members remain informed and aligned.