Agentic AI Engineer - Prompting & RAG (Onsite)

Emergere Technologies; Plano (TX); On-site; USD 96,000 - 165,000; Part time

Job summary

Emergere Technologies in Plano, TX is seeking an AI/ML engineer with Agentic AI experience for a contract role onsite. You will drive end-to-end ML systems, design advanced prompts, and build conversational AI capabilities for real-world applications.

The ideal candidate has 8 years of experience, strong software background, and hands-on expertise with modern LLMs, RAG, and vector databases, with focus on production-ready solutions using Python and ML frameworks.

Qualifications

• Expert prompt engineer with a strong software background and 8 years of AI/ML experience.
• Knowledge of computer vision related projects.
• Hands-on experience with modern LLMs (OpenAI, Anthropic, LLaMA, Mistral, Gemini) and tokenization concepts.
• Experience with retrieval-augmented generation and vector databases.
• Proficient in Python, PyTorch/TensorFlow, cloud services, and MLOps practices.
• Experience building conversational flows (chatbots).
• Familiar with REST APIs, JSON, YAML, and production integration of LLM prompts.
• Safety, guardrails, and compliance awareness.

Responsibilities

• Develop and deploy end-to-end ML systems and AI workflows.
• Design and optimize LLM prompts and workflows for production use.
• Build and refine conversational flows and chatbots.
• Work with embedding models, vector databases, and RAG strategies.
• Ensure safety, guardrails, and compliance in AI systems.

Skills

Prompt engineering

Software engineering

Communication

AI/ML use cases

Computer vision

LLM expertise

RAG workflows

Model evaluation

Tokenization knowledge

Python

Tools

FAISS

Milvus

Pinecone

OpenAI

Anthropic

LLaMA

Mistral

Gemini

PyTorch

TensorFlow

Job description

Emergere Technologies in Plano, TX is seeking an AI/ML engineer with Agentic AI experience for a contract role onsite. You will drive end-to-end ML systems, design advanced prompts, and build conversational AI capabilities for real-world applications.

The ideal candidate has 8 years of experience, strong software background, and hands-on expertise with modern LLMs, RAG, and vector databases, with focus on production-ready solutions using Python and ML frameworks.