Embedded Systems Engineer Salary Guide 2026

Two embedded systems engineers examining a green printed circuit board together in a hardware lab

By Tom Kenaley, Senior Partner and President, KORE1 Embedded systems engineer pay in 2026 lands between $91,000 and $161,000 across the major salary sources. Change the question to who employs them and the same title spans $106,000 to $331,000. That second spread decides whether your search closes. On a single afternoon in August 2026 I … Read more

Why “Tech Debt” Is the Wrong Frame: Renaming the Problem to Get the Resources

Engineering executive presenting a technical debt funding request to three seated executives in a boardroom

By Kris Drouet, Engineering Executive, in partnership with KORE1 Selling tech debt to executives fails because the phrase names four unrelated problems at once. Split it into security exposure, delivery cost, key-person risk, and a growth ceiling, then bring the one your CFO already funds. I have watched the same request get denied and then … Read more

AI Code Review for Engineering Teams: A VP’s Guide to Not Becoming the Bottleneck

Vice President of Engineering standing in a modern office hallway, representing engineering leadership on AI code review governance

By Kris Drouet, Engineering Executive, in partnership with KORE1 AI code review works for engineering teams when a VP assigns a named human owner to every risk tier, sets a review SLA the team tracks weekly, and reserves final judgment for changes touching trust boundaries, money, or production access. That’s the entire operating model in … Read more

When to Buy and Then Build On Top: The Most Underused AI Pattern in Mortgage Tech

Engineering executive weighing how much of a vendor AI platform to trust versus build custom on top

By Kris Drouet, Engineering Executive, in partnership with KORE1 Buy the vendor’s AI for the seventy percent every lender needs, document intake, underwriting signals, compliance logging, and build custom only at the one exception queue that is actually yours. Most engineering leaders pick one extreme or the other. The pattern that actually works sits in … Read more

Fintech Engineering Velocity Without Audit Pain: 3 Patterns That Actually Work

Fintech engineering VP who keeps release velocity high through audits with a risk-tiered change process

By Kris Drouet, Engineering Executive, in partnership with KORE1 Fintech engineering teams keep velocity through an audit by making evidence a byproduct of the pipeline, tiering changes by risk instead of reviewing everything equally, and documenting a break-glass path before they need it. Three patterns. I have shipped under all three, auditors have signed off … Read more

The Real Cost of a Synchronous API in a Pub/Sub World

Empty conference room at dusk with a whiteboard of boxes and arrows after an architecture review

By Kris Drouet, Engineering Executive, in partnership with KORE1 A synchronous call inside an event-driven system costs you the product of every dependency’s availability, the worst tail latency anywhere in the chain, and the retry load of every client sitting above it. Three numbers. You can compute all three in an afternoon from data you … Read more

The Sprint Plan That Acts Like a Contract: How to Treat Estimates as Informed Commitments

Empty engineering sprint planning room with a blank whiteboard and orange accent wall before a planning session

By Kris Drouet, Engineering Executive, in partnership with KORE1 An estimate becomes an informed commitment when it names its assumptions, carries a range instead of one date, and comes with a standing right to renegotiate scope the moment an assumption breaks. An aspirational guess carries none of that. It carries a date and a hope. … Read more

The Vendor Demo Trap: Why Your Best Engineers Can’t Tell If an AI Pitch Is Real

Two engineering leaders reviewing an AI vendor proposal on printed documents in a conference room

By Kris Drouet, Engineering Executive, in partnership with KORE1 Your best engineers cannot reliably evaluate an AI vendor demo, because the demo is a controlled performance and their own judgment about AI is measurably unreliable. In a 2025 randomized trial, experienced developers ran 19% slower with AI tools while believing they had run 20% faster. … Read more