AI Engineer I at Quality Technology Services, LLC
Suwanee, GA
—
Jul 17, 2026
Suwanee, GA
Jul 21, 2026
What this job asks for AI summary
An entry-level engineering role focused on building and maintaining components of LLM-based applications, including integrating AI model APIs, constructing retrieval-augmented generation pipelines, and supporting data preparation. The position sits within an AI and analytics team, working alongside senior engineers and data scientists. It suits early-career developers with Python experience and some hands-on exposure to LLM APIs.
Junior level · National · Full-time
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $138,970 (middle half $107,524–$175,762).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (8)
No work location or metro area is specified in the posting; CBSA fields are left blank. The role is associated with QTS Data Centers, which has facilities in multiple US markets.
The 'AI Engineer I' title and the 0–2 years experience gate firmly place this at the Junior level; the posting also explicitly states 'under the guidance of senior engineers.'
The Basic Qualifications accept either 0–2 years of hands-on experience OR a BS in CS/equivalent — because equivalent experience is explicitly accepted in lieu of the degree, the degree requirement is set to None.
SOC classification is Medium confidence: the role is primarily application software development (integrating LLM APIs, building RAG pipelines, writing code), which maps to Software Developers (15-1252). However, the data science and ML-adjacent work (embeddings, evaluation, model APIs) makes 15-2051 Data Scientists a plausible runner-up.
Prompt engineering and LLM API exposure are listed as required in Basic Qualifications but describe the same underlying 'LLMs' skill; they are consolidated into one skill entry rather than split artificially.
Vector database familiarity (pgvector, Pinecone, Chroma, Qdrant) and LLM orchestration frameworks (LangChain, LlamaIndex, LangGraph) appear under Preferred Qualifications only.
Cloud platforms (AWS/Azure) and Docker appear under Preferred Qualifications only.
Hugging Face and Ollama appear under Preferred Qualifications as examples of open-source/locally run model tooling.
Read the full posting
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