AI Deployment Engineer

The deep technical engine behind our internal AI deployment team. Where the AI Deployment Strategist scopes and builds agents, you own the infrastructure underneath — data pipelines, system integrations, and everything that ensures deployed AI solutions work reliably at scale.

You will take prototypes to production, ensure all business systems communicate correctly, and build the technical backbone that our AI tooling depends on.

Responsibilities

• Own the data infrastructure underpinning AI deployments — pipelines, storage, and data serving
• Integrate AI solutions into the existing business ecosystem: CRMs, ERPs, SaaS tools, and internal systems
• Build and maintain APIs, webhooks, and middleware that allow AI agents to interact with business systems
• Take Strategist-built prototypes to production-grade — hardening, scaling, and ensuring reliability
• Set up monitoring, logging, and alerting across deployed pipelines and agent infrastructure
• Manage data models, schemas, and storage supporting current and future AI deployments
• Troubleshoot integration failures, data inconsistencies, and production issues

Skills

• Python & SQL (production-grade pipeline development)
• REST APIs, webhooks, OAuth, event-driven architecture
• Orchestration tools: Airflow, Prefect, or Dagster
• Cloud platforms: AWS, GCP, or Azure
• Docker & Kubernetes Microsoft 365 & Microsoft Copilot

Desirable skills

• Vector databases and embedding pipelines
• Real-time streaming (Kafka, Flink)
• RPA tooling (UiPath, Power Automate) dbt for data transformation
• Claude Code, Claude Cowork, or Claude Skills
• Experience with vector databases, real-time streaming (Kafka, Flink), or RPA tooling (UiPath, Power Automate)

Experience

3–5 years in software or data engineering with strong exposure to system