Client‑Facing AI Deployment Engineer

CloudFactory; Seattle (WA); On-site; USD 110,000 - 160,000; Full time

Job summary

CloudFactory is seeking an engineer to design and implement scalable AI deployment architectures with client-facing responsibilities. You will build APIs, data pipelines, and integrations, while coordinating with delivery teams to scale production workflows.

We value 2+ years of software engineering experience, strong Python and Go skills, cloud infrastructure knowledge (AWS/GCP/Azure), and the ability to translate complex needs for executives and technical teams.

Qualifications

• 2+ years of software engineering experience.
• Strong Python and Go proficiency.
• Experience with Claude and relevant AI tools.
• Experience with cloud infrastructure (AWS/GCP/Azure).
• Experience building APIs and distributed systems.
• Ability to communicate with both executive and technical stakeholders.

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.
• Build APIs, connectors, automation scripts, and data pipelines.
• Debug integration issues in client environments.
• Contribute to internal platform enhancements.
• Surface recurring patterns from client deployments.
• Lead technical discovery sessions.
• Support pre-sales validation.
• Act as trusted advisor to enterprise engineering teams.

Skills

Python

Go

APIs

Distributed systems

Client communication

Tools

Claude

AWS

GCP

Azure

Job description

CloudFactory is seeking an engineer to design and implement scalable AI deployment architectures with client-facing responsibilities. You will build APIs, data pipelines, and integrations, while coordinating with delivery teams to scale production workflows.

We value 2+ years of software engineering experience, strong Python and Go skills, cloud infrastructure knowledge (AWS/GCP/Azure), and the ability to translate complex needs for executives and technical teams.