Overview
On Site
Depends on Experience
Full Time
Skills
GCP
ASW
Azure
Vertex AI
GenAI
LLaMA
Job Details
Job Role - Generative AI Engineer
Location - Richardson, TX (Onsite - Hybrid)
Job Type - Open for both contract/ Full Time
Minimum Exp - 8+ Years
Visa: OPT, and L2s
Note - Candidate should be from good Academic Background
Vetting Flow
1. Technical interview
2. 15 minutes Delivery connect
3. 1 hour Face to face at Richardson, TX (Client interview)
As a Generative AI Engineer, you ll be a core member of this pod, building and integrating agentic systems powered by cutting-edge LLM and GenAI technologies. You ll 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 pod s technical roadmap.
Core Skills & Experience
Must Haves
- 4 8 years of software engineering experience with at least 1 2 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, AutoGen, CrewAI is a must
- Understanding of Git, CI/CD, DevOps, and production-grade GenAI deployment practices.
Nice-to-Have
- Familiarity with Google Cloud Platform (Google Cloud Platform) especially Vertex AI, Cloud Run, and GKE.
- 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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.