AI & Automation Engineer: Scalable Data Pipelines

Synapse SEM; Boston, Northern (MA, KY); Hybrid; USD 140,000 - 200,000; Full time

Job summary

Synapse Labs in Boston, MA, seeks an AI/Automation Engineer to design and build back-end systems powering internal automation and marketing intelligence. You will translate business ideas into scalable data pipelines, cloud workflows, and production-grade services, with significant autonomy in shaping architecture.

Collaborating with strategy and marketing teams, you will reduce manual bottlenecks, implement reliable ingestion, and drive CI/CD and observability across deployments.

Qualifications

• Strong Python experience building production-grade backend systems.
• Deep knowledge of SQL and cloud data warehouses (BigQuery preferred).
• Experience integrating third-party APIs and designing reliable ingestion workflows.
• Hands-on with serverless or containerized workloads (GCP/AWS).
• Experience with logging, monitoring, and alerting in production systems.

Responsibilities

• Design and build backend systems that automate marketing workflows and reporting.
• Build and maintain structured data pipelines ingesting large volumes of data.
• Ensure automated deployments and consistent Dev/Stage/Prod environments.
• Deploy and manage automation workloads in cloud environments (GCP preferred).
• Improve CI/CD, containerization, and environment structure.
• Collaborate with marketing strategists to translate business requirements into durable technical solutions.

Skills

Python

SQL

APIs

Cloud

Observability

Education

B.S. in Computer Science or Engineering

Tools

Docker

BigQuery

GCP

AWS

CI/CD

Job description

Synapse Labs in Boston, MA, seeks an AI/Automation Engineer to design and build back-end systems powering internal automation and marketing intelligence. You will translate business ideas into scalable data pipelines, cloud workflows, and production-grade services, with significant autonomy in shaping architecture.

Collaborating with strategy and marketing teams, you will reduce manual bottlenecks, implement reliable ingestion, and drive CI/CD and observability across deployments.