AI Deployment Engineer — Client-Facing & Production-Ready

CloudFactory; Town of Texas (WI); On-site; USD 120,000 - 180,000; Full time

Job summary

CloudFactory is an AI enablement company helping enterprises deploy AI at scale. You will design and implement integrations between client systems and CloudFactory’s platform, build API connectors and data pipelines, and lead technical discussions with enterprise engineering teams.

The role blends hands-on engineering with product awareness, requiring in-depth knowledge of Python, Go, cloud infrastructure, and AI tooling. Occasional travel to client sites is expected as projects scale.

Qualifications

• 2+ years software engineering experience.
• Strong proficiency in Python and Go.
• Proficiency with Claude and all relevant AI tools.
• Experience with cloud infrastructure (AWS/GCP/Azure).
• Experience building APIs and working with distributed systems.
• Experience designing data pipelines or ML infrastructure.
• Ability to translate ambiguity into architecture.

Responsibilities

• Design and implement integrations between client systems and CloudFactory’s platform.
• Architect scalable agentic AI & human-in-the-loop workflows.
• Define data ingestion, transformation, and feedback loops.
• Evaluate system bottlenecks (latency, quality, throughput).
• Translate proof-of-concept AI systems into scalable production workflows.
• Identify operational risks before deployment.
• Partner with Delivery teams to ensure execution feasibility.
• Improve reliability and reduce manual intervention.
• Lead technical discovery sessions and support pre-sales validation.

Skills

Python

Go

Claude

Cloud platforms

APIs

Distributed systems

Data pipelines

Architecture

Tools

AWS

GCP

Azure

Job description

CloudFactory is an AI enablement company helping enterprises deploy AI at scale. You will design and implement integrations between client systems and CloudFactory’s platform, build API connectors and data pipelines, and lead technical discussions with enterprise engineering teams.

The role blends hands-on engineering with product awareness, requiring in-depth knowledge of Python, Go, cloud infrastructure, and AI tooling. Occasional travel to client sites is expected as projects scale.