Austin, TX

Salary
Posted
Jul 21, 2026
Location
Austin, TX
Last confirmed open
Jul 29, 2026

What this job asks for AI summary

A short-term staff augmentation role at a state public safety agency, focused on several concurrent AI initiatives. Day-to-day work spans building and deploying parts of an enterprise search tool, configuring and documenting an AI inventory system, implementing and testing AI agents for business units, and developing technical controls and documentation to support AI governance adoption.

Mid level · 1+ years · Austin-Round Rock-Georgetown, TX · Contract

Must have (3)
enterprise search · 1+ yrsDarwin AI · 1+ yrsAI agents · 1+ yrs

We read this from the posting text with AI. Skim the description below before ruling yourself out.

Why we read it this way (9)

This is a short-term staff augmentation (contract) engagement at the Texas Department of Public Safety (DPS), supporting active AI/ML initiatives.

The posting is unusually sparse on named technologies. The four skill areas listed are derived directly from the four 'Required' line items in the qualifications table, each calling for 1 year of experience.

Darwin AI is named as a specific inventory system being rolled out; it is the only concrete product name in the posting.

'Enterprise search tool' and 'AI agents' are functional descriptions rather than named products — no specific platform (e.g., Elasticsearch, Azure AI Search, LangChain) is identified.

SOC classification is Medium confidence: the role blends ML/AI engineering (15-2051) with software build-and-deploy work (15-1252); 15-1252 was chosen as primary given the emphasis on building, deploying, and implementing components rather than modeling or research.

Location is inferred as Austin, TX, the headquarters of Texas DPS; no explicit city is stated in the posting.

No compensation, degree, or clearance requirements are stated.

Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): AI governance.

Posting is for a contract engagement — the market benchmarks below price full-time roles, so read the comp comparison with that in mind.

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