Founding engineers, staff/principal ICs, engineering managers, VPs, and AI-native builders for Seed through Series C startups. The honest guide to hiring engineering talent in the post-2023 market — what roles to hire, what they cost, and how long it takes.
The engineering hiring market changed in 2023 and hasn't gone back. Generalist supply expanded, AI talent decoupled, and the bar at every level moved up. This page is the unvarnished version of what we tell every founder who hires us — what roles exist, what they cost, how long they take, and what tradeoffs actually matter.
Every VC-backed startup has roughly the same ladder, with two big variations: whether you have an IC track separate from management, and whether you've grown to the point where Staff and Principal mean different things. Here is the working taxonomy we use across all our searches.
Employees #1–5. Generalist range, product-mindset, ships to prod weekly. Often the only senior engineer in the building until ~10 heads.
5–8 years experience. Owns features end-to-end, mentors juniors, is trusted on architecture decisions inside one team.
First company-wide impact level. Owns a major surface area or platform, calibrates the bar, unblocks the org without managing people.
Technical direction across multiple teams. Usually appears once eng org passes ~40 heads. Sets architectural standards.
Owns a team of 4–10. People management + delivery + on-call ownership. The hardest role to hire well; very high variance.
Multiple teams or a major product line. Bridges VP-level strategy and EM-level execution. Often loaded onto the second functional area.
Owns the entire engineering org. Hiring, process, on-call, delivery, and the leadership team. Most common at 15–80 engineers.
Technical vision, architecture, build vs. buy, hiring bar. At early stage, often the most senior engineer; at later stage, often externally-facing.
Short answer: 6–10 weeks end-to-end for most searches. Founding engineer and senior leadership searches sit at the long end. Mid-level IC searches in well-defined stacks close faster.
Here is the realistic decomposition:
| Phase | What happens | Typical duration |
|---|---|---|
| Intake & calibration | Job scope, bar, comp band, scorecard, sample candidates. | 3–7 days |
| Sourcing & outreach | Build the market map, outreach, first conversations. | 2–3 weeks |
| Screens & loops | Recruiter screen → hiring manager → technical → onsite. | 2–3 weeks |
| Offer & close | Negotiation, references, accept, counter-offers, signed. | 1–2 weeks |
| Notice period | Signed → start date. Founding/senior hires often longer. | 2–6 weeks |
Source: Nxt Level internal data across 2,000+ placements at VC-backed companies.
What makes a search slow: undefined scorecard, more than 5 interview steps, missing hiring-manager bandwidth, comp band well below market, or an interview loop that doesn't reflect the real job.
What makes a search fast: a clear "must-have vs nice-to-have," a 4-step loop with the same panel, ≤5-day turnaround on every step, and a hiring manager who replies to debriefs the same day.
All ranges below assume US-based, remote-or-hybrid, post-Series A. Pre-seed and seed roles compress base and expand equity. SF/NYC sit at the top of the range; the rest of the US sits in the middle; lower-cost metros compress base ~10–15%.
| Role | Stage | Base (USD) | Equity (%) | Realistic total comp* |
|---|---|---|---|---|
| Founding Engineer | Pre-seed / Seed | $160K – $200K | 0.50% – 2.00% | $200K – $300K |
| Senior Engineer | Series A | $170K – $220K | 0.10% – 0.30% | $210K – $290K |
| Senior Engineer | Series B / C | $190K – $240K | 0.05% – 0.15% | $240K – $340K |
| Staff Engineer | Series A | $200K – $245K | 0.20% – 0.45% | $260K – $360K |
| Staff Engineer | Series B / C | $220K – $280K | 0.10% – 0.25% | $310K – $440K |
| Principal Engineer | Series C+ | $260K – $320K | 0.10% – 0.25% | $380K – $540K |
| Engineering Manager | Series A / B | $210K – $260K | 0.15% – 0.40% | $290K – $410K |
| VP Engineering | Series B | $260K – $320K | 0.50% – 1.00% | $400K – $650K |
| VP Engineering | Series C | $280K – $360K | 0.30% – 0.70% | $500K – $800K |
| AI / ML Engineer (Sr) | Series A–C | $220K – $320K | 0.10% – 0.30% | $400K – $650K |
*Total comp uses a 4-year vesting view at a realistic exit value (not the 409A and not the last preferred). For more granular numbers including signing bonus and how to discount equity, use our offer calculator.
If you want to translate your specific offer into a number candidates will understand, the market data and offer calculator page does it in one screen.
A "founding engineer" is one of the most abused job titles in startup hiring. We use a strict definition: employees #1–5, hired before product-market fit, with meaningful equity. That's the only setup where the title is honest.
At a US Pre-seed or Seed company in 2026, founding engineer offers cluster in this range:
| Position | Base | Equity | Typical total |
|---|---|---|---|
| Employee #1 (true founding) | $160K – $190K | 1.00% – 2.00% | $210K – $310K |
| Employee #2–3 | $170K – $200K | 0.50% – 1.00% | $200K – $290K |
| Employee #4–5 | $180K – $210K | 0.25% – 0.60% | $200K – $280K |
The honest signal isn't "we raised" — it's "staying small is slowing us down." Most strong founders make the hire 3–6 months post-seed, after they've found enough product signal that the next 3–6 months of velocity genuinely matters.
Active design partners, a backlog you can't ship, and the next quarter's velocity will compound for the round you're raising.
You're still hunting for the wedge. Hiring now dilutes equity, anchors your stack, and adds management overhead before you need it.
In the FAANG ladder, both are senior IC levels — Staff is L6, Principal is L7. At a startup, those titles arrive earlier and mean less, until the engineering org passes ~40 heads. Here's the working distinction we use.
| Dimension | Staff Engineer | Principal Engineer |
|---|---|---|
| Scope | Owns a major surface area or platform. | Sets technical direction across multiple teams. |
| Time horizon | 1–2 quarters. | 2–6 quarters. |
| Influence | Calibrates the bar inside the org. | Sets the bar; recruits Staff engineers. |
| Typical comp | $220K – $280K base · 0.10–0.25% eq | $260K – $320K base · 0.10–0.25% eq |
| When it appears | Series A onward. | Series C onward (~40+ engineers). |
Practical advice for founders: If you're a Series A/B with under 40 engineers, you almost certainly don't need a Principal level on your ladder yet. The signal you need a Principal is when two or more Staff engineers are blocking on the same architectural question and no one is empowered to break the tie.
Since 2023, AI talent has fully decoupled from generalist engineering. The market has effectively split into three tiers, each with different ranges and different sourcing playbooks.
| Tier | Profile | Base | Realistic total |
|---|---|---|---|
| Applied AI Engineer | Builds with LLM APIs, eval pipelines, RAG, agents. | $200K – $260K | $320K – $480K |
| ML Engineer | Trains, fine-tunes, deploys models. PyTorch/TF in production. | $220K – $300K | $380K – $560K |
| Frontier-lab Research Eng | OpenAI / Anthropic / DeepMind / FAIR alumni. | $300K – $450K+ | $650K – $1.2M+ |
Frontier-lab packages assume Series B+ companies with cash to match. At Series A, the realistic ceiling is usually capped by your runway, not the candidate.
The terms "ML engineer" and "AI engineer" are now used interchangeably in job posts but mean different things to candidates. Use these working definitions in your scorecard:
Builds features on top of foundation models. Strong product instinct, good at prompt engineering and evals, ships LLM-powered features users actually touch.
Trains, fine-tunes, deploys models. Deep on infrastructure (GPUs, distributed training), eval rigor, data pipelines, and model performance.
The two most-confused leadership titles in early-stage engineering. The answer depends almost entirely on who you already are.
Hire the CTO first. They own technical vision, early architecture, build vs. buy decisions, and — critically — the hiring bar for everyone after them. This person will be a co-founder in everything but title and should get co-founder-level equity (often 3–10%).
Your next leadership hire is almost always a VP Engineering, not a second technical voice. The VP owns execution: hiring, process, on-call, delivery, and the eng leadership team. The trigger point is typically 15–25 engineers, when delivery and people management start consuming more than 40% of your week.
| Trait | CTO | VP Engineering |
|---|---|---|
| Owns | Technical vision, architecture, build vs. buy. | Execution, hiring, process, delivery. |
| Typical first hire | ~5 engineers. | ~15–25 engineers. |
| Equity range | 0.5% – 10%+ (varies wildly with founding status). | 0.3% – 1.2%. |
| Base range | $240K – $380K | $260K – $360K |
| External signaling | Yes — speaks for the company's tech. | Mostly internal. |
When staying small is actively slowing the company down — not when you've raised. Most strong founders make their first non-founder engineering hire 3–6 months post-seed, after they have enough product signal that the next 3–6 months of velocity actually matters.
6–10 weeks end-to-end is typical: ~1 week intake, 2–3 weeks sourcing, 2–3 weeks interviews, 1–2 weeks offer/close. Founding and senior leadership searches sit at the long end; mid-level IC searches in well-defined stacks close faster.
$160K–$220K base with 0.5%–2.0% equity is the typical range at US VC-backed Pre-seed/Seed companies. Total comp on a realistic outcome lands $200K–$320K. Higher base + lower equity skews to Seed; lower base + higher equity skews to Pre-seed.
Yes, but the math is different. H1B sponsorship adds $5K–$15K in legal cost and lengthens the time-to-start by 2–6 months depending on lottery timing. Most Series A+ startups will sponsor for senior/staff roles; many Pre-seed/Seed companies won't.
For senior engineers in LATAM and Eastern Europe, base is typically 30–50% lower than US comp. The hidden costs: timezone overlap, equity treatment, IP assignment, and management overhead. For a 5-person founding team, near-shore rarely pays off; for an established 30+ person eng org, it can.
Retained for senior leadership (VP/CTO) and any hire where confidentiality or calibration matters. Contingent works for ICs through senior manager when you want optionality and only pay on hire. We do both — see the home page for our two engagement models.
At Series A–C startups, senior AI/ML engineers run $220K–$320K base with realistic total comp of $400K–$650K. Frontier-lab alumni (OpenAI, Anthropic, DeepMind) command 30–50% premiums on top of that.
