← Search all jobs

Forward Deployed Engineer

CloudFactory

Dallas, TX · Posted October 28, 2026

Just laid off? Start here: a plan for the first weeks

See every open role at CloudFactory

More in Texas job market · All Forward Deployed Engineer jobs (327) · Retail & E-commerce · Engineering jobs

More roles at CloudFactory

Similar jobs

Where Dallas, TX ranks

Where Dallas, TX placed in our monthly rankings, month by month. Each month stays online at its own address.

Pay compared with the market

This listing does not state pay. Across 120 open forward deployed engineer listings that state pay, the middle half runs $155,000 to $237,500 and the median is $197,500.

Listed pay is what employers advertise, not what people are paid.

Forward Deployed Engineer salaries by state · Check your own pay

How AI is used in this kind of work

Among software developers, AI is already used for some of the tasks. Measured exposure for software developers: 29% (some).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

Check how this applies to your own job

Skills this job asks for

Say which you have and which you want to build. We use it to match you to jobs like this one.

  • Python
  • AWS
  • Azure
  • GCP

About the job

At CloudFactory, we are a mission-driven team passionate about unlocking the potential of AI to transform the world. By combining advanced technology with a global network of talented people, we make unusable data usable, driving real-world impact at scale.

More than just a workplace, we’re a global community founded on strong relationships and the belief that meaningful work transforms lives. Our commitment to earning, learning, and serving fuels everything we do as we strive to connect one million people to meaningful work and build leaders worth following.

Our Culture

At CloudFactory, we believe in building a workplace where everyone feels empowered, valued, and inspired to bring their authentic selves to work. We are:

Mission-Driven: We focus on creating economic and social impact.

People-Centric: We care deeply about our team’s growth, well-being, and sense of belonging.

Innovative: We embrace change and find better ways to do things together.

Globally Connected: We foster collaboration between diverse cultures and perspectives.

If you’re passionate about innovation, collaboration, and making a real impact, we’d love to have you on board!

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

Boston, MA

New York, NY

Seattle, WA

Chicago, IL

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

Requirements

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