Staff Engineer - AI Engineer at Nagarro
Grand-Prairie, TX
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Jul 28, 2026
Grand-Prairie, TX
Jul 29, 2026
What this job asks for AI summary
This onsite AI Engineer role at a digital product engineering firm in Grand Prairie, TX focuses on building and deploying AI/ML solutions for manufacturing environments. The work centers on architecting RAG pipelines, integrating LLMs into enterprise cloud systems, and bridging OT/IT data from shop-floor systems (MES, SCADA, ERP) to drive operational improvements. It suits an experienced engineer comfortable with both industrial protocols and modern generative AI tooling.
Senior level · 6+ years · Dallas-Fort Worth-Arlington, TX · 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
Roughly 9 people in the Dallas-Fort Worth-Arlington, TX area plausibly meet what this posting asks for (data scientists). range 3–15
Applicant volume Light — Few people clear these requirements, so an application that does clear them gets looked at. Worth applying to even if you miss a nice-to-have.
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $130,559 (middle half $92,500–$149,977).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 29, 2026. It is a model, not a headcount.
Why we read it this way (5)
The 6–9 years of overall AI engineering experience is stated as a hard gate in the Must Have section; the overall years minimum is set to 6 (the lower bound).
Manufacturing domain experience (2–4 years) is explicitly marked 'Optional' in the job overview, so it is treated as preferred despite MES/SCADA/ERP appearing in the Must Have block — the Must Have block gates on shop-floor systems knowledge broadly, not the domain tenure specifically.
Industrial protocols (OPC-UA, MQTT, Modbus) appear only in the narrative/overview section, not in the Must Have block, so they are treated as preferred. They are listed as separate skills rather than a single combined skill because each is a distinct protocol.
OEE, Six Sigma, SPC, and lean methodologies are mentioned in the narrative but name no specific software tool, so they are omitted per the no-generic-concepts rule.
The role is classified as Data Scientists (15-2051) given the primary focus on LLM/AI model work and RAG pipeline architecture; Software Developers (15-1252) is the runner-up given the engineering and integration emphasis.
Read the full posting
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