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Software Engineer, Full-Stack + Data

Job in Franklin, Williamson County, Tennessee, 37068, USA
Listing for: National Data Solutions
Full Time position
Listed on 2026-08-22
Job specializations:
  • Software Development
    Python, Backend Developer, Front End Developer, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 55000 - 75000 USD Yearly USD 55000.00 75000.00 YEAR
Job Description & How to Apply Below

This is entry level, but it is not a sit-in-the-corner-and-do-tickets job. This is a small team where everyone has real ownership and direct access to the people who need to know what you're working on, and there is no layer of process between you and them. You will work across the full stack (Angular on the front end, Node.js and Python on the back end) and, because the work is heavily data-driven, you will also build and maintain data pipelines and write real SQL alongside application code, not as a separate specialty bolted on.

We do not expect you to know everything already. We expect you to be confident in your ability to figure things out: to read the docs, dig into the code, run an experiment, and ask a well-formed question when you're genuinely stuck rather than spinning silently for two days or guessing and hoping. What matters more than which specific language or framework you already know is whether you can reason through a problem and get the details right, whether you write every line yourself or use an AI tool to help you get there.

AI is expected to be part of how you work, not a substitute for understanding your own code. You should be able to explain and defend anything you ship, in plain language, to the people relying on it, including non-technical stakeholders.

Here's the honest part: the technical list below is close to table stakes at this point. An AI tool can execute most of it in about the same amount of time whether the person directing it genuinely understands the problem or not. What has actually separated people who thrive here from people who don't is not the checklist. It's how you figure things out when nobody's handed you the answer, and whether you can bounce between a data pipeline problem, a front-end feature, and an unrelated question from a teammate in the same day without losing your footing on any of them.

If you do your best work locked into one problem for long uninterrupted stretches and find it genuinely disruptive to switch contexts often, that's worth being honest with yourself about before applying.

What this role actually does

Read this before you apply

This is entry level, but it is not a sit-in-the-corner-and-do-tickets job. This is a small team where everyone has real ownership and direct access to the people who need to know what you're working on, and there is no layer of process between you and them. You will work across the full stack (Angular on the front end, Node.js and Python on the back end) and, because the work is heavily data-driven, you will also build and maintain data pipelines and write real SQL alongside application code, not as a separate specialty bolted on.

We do not expect you to know everything already. We expect you to be confident in your ability to figure things out: to read the docs, dig into the code, run an experiment, and ask a well-formed question when you're genuinely stuck rather than spinning silently for two days or guessing and hoping. What matters more than which specific language or framework you already know is whether you can reason through a problem and get the details right, whether you write every line yourself or use an AI tool to help you get there.

AI is expected to be part of how you work, not a substitute for understanding your own code. You should be able to explain and defend anything you ship, in plain language, to the people relying on it, including non-technical stakeholders.

Here's the honest part: the technical list below is close to table stakes at this point. An AI tool can execute most of it in about the same amount of time whether the person directing it genuinely understands the problem or not. What has actually separated people who thrive here from people who don't is not the checklist. It's how you figure things out when nobody's handed you the answer, and whether you can bounce between a data pipeline problem, a front-end feature, and an unrelated question from a teammate in the same day without losing your footing on any of them.

If you do your best work locked into one problem for long uninterrupted stretches and find it genuinely disruptive to switch contexts often, that's worth being honest with yourself about before applying.

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