Role Summary:Cloudfactory is an AI enablement company where our software platform enables trusted AI at scale. Services of the platform include data preprocessing, AI model fine-tuning, inference oversight and MLOps for AI solutions in production. For traditional enterprises that have an aspiration to leverage AI to disrupt their industries but lack the skills or capabilities needed to design, prove, develop and deploy AI solutions we offer Forward deployed Engineering services that can advise, design, prove, develop, scale and operate AI solutions for them.
You will work directly with strategic clients to design and implement scalable technical integrations, define production-ready workflows, and ensure AI systems transition from experimentation to reliable deployment.
This is a hands-on engineering role with strong product and client-facing responsibilities.
Location & Travel:- Preferred location: Dallas, TX
- Relocation assistance available for qualified candidates
- Frequent travel to client sites may be required (depending on client needs)
Responsibilities: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
RequirementsEngineering 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 12 inference 12 evaluation 12 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
Benefits 
