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# Forward Deployed Engineer

- **Company:** CloudFactory Limited
- **Location:** Chicago, IL, United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Automation of Tests, Microsoft Azure, Cloud Computing, Software Debugging, Distributed Systems, Python (Programming Language), Software Deployment, Software Engineering, Data Ingestion, Machine Learning Operations, Api Design, Data Pipelines
- **Published:** September 4, 2026
- **Apply:** https://www.careerjet.com/jobad/us68b2ad181117e58b225e163073ec6b7c

## About the Role

Engineering depth:

 * 2+ years software engineering experience
 * Strong proficiency in Python, Go
 * Proficiency with Claude and all relevant AI tools
 * Experience with cloud infrastructure (AWS/GCP/Azure)
 * Experience building APIs and working with distributed systems

Systems thinking:

 * Experience designing data pipelines or ML infrastructure
 * Ability to evaluate end-to-end workflow performance
 * Familiarity with AI/ML lifecycle (training * inference * evaluation * feedback)

Product judgement:

 * Ability to differentiate scalable feature opportunities from custom requests
 * Strong prioritization instincts

Communication:

 * Ability to communicate with C-level and deeply technical stakeholders
 * Comfortable running technical workshops
 * Able to translate ambiguity into architecture

## Description

AI Deployment Architecture:

 * 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)

Product Readiness & Scale:

 * 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

Hands-on Engineering:

 * Build APIs, connectors, automation scripts, and data pipelines
 * Debug integration issues in client environments
 * Contribute to internal platform enhancements

Field Product Intelligence:

 * Surface recurring patterns from client deployments
 * Distinguish between custom solutions and reusable features
 * Influence roadmap priorities with evidence from the field

Technical Leadership:

 * Lead technical discovery sessions
 * Support pre-sales validation
 * Act as trusted advisor to enterprise engineering teams


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