Charlotte QA Job Market Intel

One of the more interesting conversations I sat in on recently wasn’t about building AI workflows. It was about maintaining them.

Ovidius AI was discussing a challenge I think a lot of AI implementation firms run into:

How do you maintain delivery quality as AI systems become more complex?

The workflows themselves weren’t the issue. The team already builds across tools like N8N, Next.js, Supabase, and multiple LLMs.

The challenge was operational:

regression testing,
edge cases,
inconsistent AI outputs,
error categorization,
and building QA processes that don’t cost as much as the projects themselves.

That led to an interesting discussion with Ben Fellows and the team @ LoopQA around what QA for AI systems actually looks like in practice.

Not just “does this app work,” but:

• how to design reusable test harnesses
• where AI-generated test cases fit
• how to think about deterministic vs. generative outputs
• and how teams build trust and operational visibility around AI-driven workflows

It feels like a lot of companies are entering a new phase of AI adoption. The challenge is no longer just building workflows. It’s figuring out how to scale, validate, and trust them in production.

Thanks to Jason / Ben & team for the practical discussion.

Seeing continued demand for senior-level Quality Engineers with automation experience, particularly around modern QA practices, automation coverage, and supporting evolving engineering workflows which is exciting to see.

Example: Hearing TQL recently interviewed for this role and believe this is more of a backfill for an existing team than a broader hiring push. Big but exciting shoes to fill. The role still appears to be open on their website. Definately worth checking out. Click HERE
Charlotte, NC
Salary Listed: $85,000 –  $110,000 base salary, benefits package, and company perks

**I do not manage or oversee this position**

If you’re applying to jobs without also reaching out to recruiters or hiring managers in your space, you’re leaving opportunities on the table. But knowing how and when to engage is what actually matters.

Top: what my LinkedIn inbox looks like
~8–10 messages/day.
Owen (my boss) gets about double.

Nothing wrong with the messages.
But when everything sounds the same, it all blends together.

Especially when you’re skimming between meetings…
you don’t get much time to “figure out” what someone means.

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Bottom: how I try to approach outreach

I don’t always get a response.
Some of it works, some of it doesn’t.

But the goal is simple:
if someone reads it once, they should immediately know:

• what I’m asking for
• why it matters to them

No decoding required.

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Most outreach fails because it optimizes for sounding professional instead of being understood.
Make it easy on the other person to respond.

Genuine question:
Do you think “professional language” actually helps outreach…or has it just become noise we’ve all learned to skim past?

Sample Messages:

Disclaimer: Please note these are just updates based on my conversations in the market

• Daniel Haynes : Filled a QA engineering role on his team (automation + AI driven). Looks like they have a couple software gigs open and potentially more QA work down the line.
• CPI: Heard CPI filled a QA role: supporting manual Salesforce and integration testing across sales workflows, including quotes, opportunities, and broader business operations such as install and service processes.
• LoopQA: Filled another QA Automation Engineer opening today supporting a large payroll migration initiative
• Interviews/hires @ companies like: Fastbreak, Moodys, Pratt Miller, QTL, Ovidius AI, Vanguard, WF, BoA & LPL Financial
• SystemsOne hired a local manual tester with specific payment experience for a remote gig