Role overview
Job Title: Applied AI Engineer (LLM / GenAI Product Engineer)
We are looking for Applied AI Engineers who can take large language models from concept to production and integrate them into real products.
About Us
Vertex is a leading AI Consulting and Development firm.
Founded over 25 years ago in Austin, Texas, Vertex began as a custom software development firm, delivering cutting-edge solutions to businesses across industries. With teams in Texas, Colorado, Africa, and India, we have built a track record of innovation and reliability.
Today, we focus on helping businesses navigate and implement AI solutions - from strategy to deployment. Whether these businesses are integrating AI into existing systems, building AI-powered products, or optimizing workflows with machine learning, we provide the guidance and technical execution needed for their success.
Our approach combines AI strategy, engineering, and DevOps to ensure seamless adoption and scalability. With a strong foundation in agile development and a commitment to collaboration, we help businesses unlock AI’s full potential.
We are now expanding our AI Experts Talent Pool, to serve our increasing number of clients and their needs.
You can learn more about us here: **https://www.vertex.com/
Job Description**
We are looking for Applied AI Engineers who can take large language models from concept to production and integrate them into real products. This is a rolling recruitment initiative for experienced AI professionals who have designed, built, and deployed production-grade AI systems in real-world environments.
This is not a single immediate hire. Candidates will undergo a structured technical vetting process. Those who meet our standards will be admitted into our AI Talent Pool and considered for full-time placements with our clients as opportunities arise.
We are specifically seeking engineers who have moved beyond experimentation and can demonstrate measurable business impact. Selection is based on technical depth, system architecture capability, production deployment experience, and professional maturity.
What you'll work on
- Design and implement LLM-powered features for real-world applications. - Build and maintain RAG pipelines, prompt workflows, and evaluation loops.
- Integrate AI systems with APIs, backend services, and data stores.
- Optimize models for latency, cost, and reliability in production.
- Collaborate with product and engineering teams to ship AI features.
What we're looking for
- Strong Python experience and backend engineering fundamentals. - Hands-on experience deploying LLMs or GenAI systems in production.
- Experience with embeddings, vector databases, and retrieval systems.
- Ability to reason about trade-offs between models, cost, and performance.
- Clear evidence of shipped AI features used by real users.