AI Engineer at Jacobs
Atlanta, GA
—
Jul 17, 2026
Atlanta, GA
Jul 21, 2026
What this job asks for AI summary
A junior role focused on building and shipping AI-powered applications and tools for government and private-sector clients, sitting within a Digital and Data team. Day-to-day work spans developing agentic workflows, RAG pipelines, and MCP server integrations, alongside full-stack contributions in Python and TypeScript. It suits an early-career developer with hands-on LLM API experience who wants to deepen expertise across the AI engineering stack.
Junior level · 1+ years · National · Bachelor's required · Full-time
“or” means any one of them counts — you don't need all of them.
Posted 2 times — it's one opening, so apply once.
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
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 $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 (6)
No work location or city is specified in the posting; Jacobs is a global firm headquartered in Dallas, TX, but this role could be based at any of their US offices. CBSA left blank.
The JD requires a Bachelor's degree with no 'or equivalent experience' escape hatch, so the degree requirement is set to Bachelors.
Travel is listed as a hard requirement under 'What You'll Need' but names no specific technology, so it is not captured as a skill.
AEC (Architecture, Engineering & Construction) industry experience appears under 'Preferred' and names no specific tool, so it is omitted from the skills list.
LangGraph is listed both as an agentic framework alternative in the responsibilities section and explicitly alongside LangChain in the requirements section; it is captured as an alternative to LangChain rather than a separate skill to avoid double-counting.
RAG pipeline experience is listed under 'Preferred' only; vector store tools (Pinecone, Weaviate, pgvector) are captured as preferred alternatives under a single vector-store skill.
Read the full posting
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