Full-Stack Software Engineer (Product) - New Grad - 2026-2027 at Netic
San Francisco, CA
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Jul 15, 2026
San Francisco, CA
Jul 21, 2026
What this job asks for AI summary
A full-stack engineering role on the product team of an AI platform serving trades and essential services businesses. Day-to-day work covers designing and shipping end-to-end features — data models, APIs, and front-end — while collaborating directly with customers to translate their workflows into product improvements. The position targets new graduates available to start between late 2026 and mid-2027, with React, TypeScript, and Python as the core stack.
Junior level · National · Full-time
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
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 (5)
This is explicitly a new-grad / entry-level hire targeting candidates available to start between winter 2026 and summer 2027, placing it firmly at the Junior band despite no level word in the title.
No work location or office city is stated in the posting; the CBSA is left blank. The company appears US-based (North America focus, US investors), so the US-based flag is set to true.
React, TypeScript, and Python are listed together under 'What You'll Bring' as a required fluency block ('Comfortable with…'), making them hard gates.
Databases and cloud infrastructure are also mentioned in the same required fluency sentence but name no specific technology, so they are omitted from the skills list per extraction rules.
LLM APIs and RAG patterns are explicitly called out as 'nice-to-have' ('AI experience (nice‑to‑have)'), so they are marked preferred. Embeddings was grouped with these but names no distinct standalone tool beyond the LLMs/RAG skills already captured.
Read the full posting
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