AI & Agent Engineer: Build Multimodel LLM Pipelines

Appnovation; Dallas (TX); On-site; USD 150,000 - 210,000; Full time

Job summary

Appnovation seeks an AI / Agent Engineer (AI Builder) to join a fast-moving team. You will craft MCP servers, tools, and graph-RAG pipelines to make documents intelligible to multiple LLMs, partnering with product, data, and QA to raise answer quality and grounding.

Ideal candidates have 5 years in software engineering, 2 years in AI/ML or LLM apps, strong Python, and experience with MCP servers, RAG, embeddings, and graph databases. Immediate impact in a collaborative, agile environment.

Qualifications

• Bachelor’s degree in CS, Engineering, or equivalent practical experience.
• 5 years of software engineering experience, with 2 years in AI/ML or LLM-based applications.
• Strong Python, with hands-on experience in LLM app development.
• Direct experience building MCP servers, tools, and skills.
• Experience with RAG and graph-RAG systems, vector databases, and embeddings.

Responsibilities

• Build and evolve MCP servers, tools, and skills for multiple LLMs.
• Design and refine a graph-RAG pipeline for document representations.
• Implement retrieval across tiers and temporal replay.
• Partner with QA on eval-driven improvements to grounding.
• Write clean, production-grade code and participate in reviews.
• Collaborate with product, data, and QA in an agile model.
• Document designs, prompts, and tool interfaces for maintainability.
• Monitor deployed agents/models and iterate on performance.
• Stay current with fast-moving LLM/agent tooling.

Skills

Python

LLM development

MCP servers

Graph-RAG

Vector databases

Git

CI/CD

Problem solving

Communication

Education

Bachelor’s Degree in CS/Engineering or equivalent

Tools

Neo4j

Postgres/Supabase

VectorDBs

CI/CD pipelines

Job description

Appnovation seeks an AI / Agent Engineer (AI Builder) to join a fast-moving team. You will craft MCP servers, tools, and graph-RAG pipelines to make documents intelligible to multiple LLMs, partnering with product, data, and QA to raise answer quality and grounding.

Ideal candidates have 5 years in software engineering, 2 years in AI/ML or LLM apps, strong Python, and experience with MCP servers, RAG, embeddings, and graph databases. Immediate impact in a collaborative, agile environment.