Staff AI Engineer - Remote - USA
Company: FullStack
Location: Fort Worth, TX (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-05-29
About this role
About FullStack
FullStack is one of the fastest-growing software consultancy companies in the Americas. We deliver transformational digital solutions to top global companies and Silicon Valley startups. As an employee-first company, we focus on hiring the most talented software designers and developers by creating a positive, respectful, and supportive work environment where they can achieve their greatest potential.
We’re Most Proud Of
- Offering life-changing career opportunities to talented software professionals across the Americas.
- Building highly-skilled software development teams for hundreds of the world’s greatest companies.
- Having delivered hundreds of successful custom software solutions, which have positively impacted the lives and careers of millions of users.
- Our 4.2-star rating on GlassDoor.
- Our client Net Promoter Score of 68, twice the industry average.
The Position
We're Looking To Hire a Staff AI Engineer To Join Our Team. You'll Work With Our Incredible Clients In One Of Two Ways
- Team Augmentation: You will integrate directly into our client's team and work alongside their existing designers and engineers daily.
- Design & Build: You will work on a FullStack product team to build and deliver a product to our clients.
What We're Looking For
- 8+ years of professional AI/ML engineering experience.
- Advanced English is required.
- Successful completion of a four-year college degree is required.
- Hands-on experience building and maintaining high-performance code in production environments, moving beyond theoretical or advisory-only roles.
- Proven experience integrating AI capabilities into large-scale, existing microservice architectures and traditional engineering stacks (e.g., .NET).
- Track record of solving complex, real-world problems using recent, practical AI implementation techniques.
- Deep experience in optimizing token economics and managing context window constraints to balance cost and perfor...