FTS, in collaboration with a cutting-edge client of ours, is seeking a highly capable AI Builder to join their embedded product management ecosystem. This AI Builder will take early-stage ideas and prototypes and turn them into production-ready applications. This role is less about traditional software engineering and more about building practical AI solutions that solve real user problems. You’ll work closely with product leaders who are already experimenting with AI—stepping in to refine concepts, shape the right approach, and evolve prototypes into scalable, reliable tools that people actually use.

The ideal person naturally operates between product and technology, combining strong AI-building capability with product thinking and user empathy. You should be comfortable working in ambiguity, moving quickly from idea to execution, and making smart decisions across models, workflows, architecture, and deployment. Strong communication is essential, as this role involves collaborating with both technical and non-technical stakeholders to build useful, usable AI-driven products.

*** This is a FULLY REMOTE role ***

***Only U.S. Citizens and Green Card Holders are eligible currently**

What You’ll Do:

1. Partner closely with product leaders to understand user problems, evaluate early AI concepts, and shape practical solutions
2. Take rough ideas, prototypes, and experiments and turn them into polished, production-ready AI applications
3. Design and build end-to-end AI experiences with a strong focus on usability, workflow fit, and real-world adoption
4. Make hands-on decisions across prompting, model selection, architecture, orchestration, and deployment
5. Build and iterate on AI systems such as RAG pipelines, agent-based workflows, and automation tools
6. Work across modern AI tooling and development environments, including LLM APIs, orchestration frameworks, cloud-based tooling, and deployment platforms like Vercel
7. Collaborate directly with technical and non-technical stakeholders, clearly communicating tradeoffs, recommendations, and product decisions
8. Rapidly test, refine, and improve solutions based on feedback, usage patterns, and evolving business needs
9. Manage code and collaboration workflows through GitHub (version control, PRs, CI/CD)
10. Continuously explore new tools, models, and approaches with a builder mindset focused on shipping useful AI products

What You’ll Bring:

1. Proven experience building and shipping AI-powered applications, tools, or workflows that solve real user problems
2. Hands-on experience with modern LLM ecosystems, including prompting strategies, model behavior, and practical model tradeoffs
3. Experience designing and implementing AI systems such as RAG workflows, agent-based experiences, or multi-step orchestration pipelines
4. Strong product instinct and user-oriented thinking—you naturally consider usability, workflow design, and how people will interact with what you build
5. Ability to take ambiguous ideas or partially defined concepts and independently turn them into structured, scalable solutions
6. Comfort operating in fast-moving, less structured environments where experimentation, adaptability, and initiative are expected
7. Experience working across the full stack, including frontend, backend, APIs, and deployment workflows
8. Strong communication skills with the ability to explain technical concepts clearly to non-technical stakeholders
9. Hands-on experience with tools such as GitHub, Vercel, and modern AI-native development environments
10. Demonstrated builder mentality—someone who actively experiments, learns quickly, and can speak concretely about things they’ve built

Preferred Qualifications:

1. Background in software engineering or application development, without being limited to a traditional engineering-only mindset
2. Experience working closely with product teams or in environments where product thinking and user needs drive technical decisions
3. Familiarity with APIs, cloud services, and modern AI development ecosystems
4. Exposure to building and supporting applications in production environments with considerations around scale, reliability, and maintainability
5. Understanding of AI governance, security, and data privacy considerations in real-world business applications
6. Experience in stakeholder-facing or customer-facing environments where communication, collaboration, and adaptability are important

What Makes this Role Unique:

1. This is not a traditional engineering role focused purely on implementation—it’s a builder role centered around solving real user problems with AI
2. You’ll work closely with product leaders who are already experimenting and prototyping, helping transform early concepts into scalable products
3. The role sits at the intersection of product, user experience, and AI technology, with a strong emphasis on building useful, usable solutions
4. You’ll have the opportunity to shape how AI products are designed, built, and adopted across the organization
5. The work spans a wide range of use cases, from internal productivity tools to external AI-driven experiences, creating broad exposure and impact

What Success Looks Like:

1. You consistently turn rough ideas and early prototypes into intuitive, production-ready AI applications that deliver real value to users
2. You move quickly from concept to execution while maintaining strong judgment around usability, scalability, and practicality
3. You operate effectively between product and engineering, helping translate business needs into well-structured AI solutions
4. You communicate clearly with stakeholders and simplify complex technical concepts into actionable decisions
5. You bring a strong sense of ownership, curiosity, and experimentation to the role, continuously improving how AI solutions are built and deployed
6. You help establish scalable patterns and best practices for creating practical, user-centered AI products across the organization

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