Highbrow Technology Inc
Generative AI Engineer (Richardson)
Highbrow Technology Inc, Richardson, Texas, United States, 75080
Generative AI Engineer
57001 Richardson, TX -onsite
As a
Generative AI Engineer , youll be a core member of this pod, building and integrating
agentic systems
powered by cutting-edge LLM and GenAI technologies. Youll work closely with Tech Leads and Full Stack Engineers to turn AI capabilities into production-ready enterprise solutions. Key Responsibilities Design, develop, and deploy
agentic AI systems
leveraging LLMs and modern AI frameworks. Integrate
GenAI models
into full-stack applications and internal workflows. Collaborate on prompt engineering, model fine-tuning, and evaluation of generative outputs. Build reusable components and services for
multi-agent orchestration
and task automation. Optimize AI inference pipelines for scalability, latency, and cost efficiency. Participate in architectural discussions, contributing to the pods technical roadmap. Core Skills & Experience Must Haves 8 years of software engineering experience with at least 2-3 years in
AI/ML or GenAI systems
in
production Hands-on experience with
Python
only for AI/ML model integration. Experience with
LLM frameworks
(LangChain, LlamaIndex is a must) Exposure to
agentic frameworks
(Langgraph, Google ADK, is a must) Understanding of
Git, CI/CD, DevOps , and production-grade GenAI deployment practices. Familiarity with
Google Cloud Platform (GCP)
e.g. Vertex AI, Cloud Run, and GKE. Good-to-Have Experience building
AI APIs, embeddings, vector search , and integrating them into applications. Experience fine-tuning open-source models (LLaMA, Mistral, etc.) or working with OpenAI APIs. Exposure to
multi-modal AI systems
(text, image, or voice). Familiarity with
Low-Code/No-Code tools
(e.g., AppSheet) for workflow integration.
As a
Generative AI Engineer , youll be a core member of this pod, building and integrating
agentic systems
powered by cutting-edge LLM and GenAI technologies. Youll work closely with Tech Leads and Full Stack Engineers to turn AI capabilities into production-ready enterprise solutions. Key Responsibilities Design, develop, and deploy
agentic AI systems
leveraging LLMs and modern AI frameworks. Integrate
GenAI models
into full-stack applications and internal workflows. Collaborate on prompt engineering, model fine-tuning, and evaluation of generative outputs. Build reusable components and services for
multi-agent orchestration
and task automation. Optimize AI inference pipelines for scalability, latency, and cost efficiency. Participate in architectural discussions, contributing to the pods technical roadmap. Core Skills & Experience Must Haves 8 years of software engineering experience with at least 2-3 years in
AI/ML or GenAI systems
in
production Hands-on experience with
Python
only for AI/ML model integration. Experience with
LLM frameworks
(LangChain, LlamaIndex is a must) Exposure to
agentic frameworks
(Langgraph, Google ADK, is a must) Understanding of
Git, CI/CD, DevOps , and production-grade GenAI deployment practices. Familiarity with
Google Cloud Platform (GCP)
e.g. Vertex AI, Cloud Run, and GKE. Good-to-Have Experience building
AI APIs, embeddings, vector search , and integrating them into applications. Experience fine-tuning open-source models (LLaMA, Mistral, etc.) or working with OpenAI APIs. Exposure to
multi-modal AI systems
(text, image, or voice). Familiarity with
Low-Code/No-Code tools
(e.g., AppSheet) for workflow integration.