Argentina 
Brazil 
Mexico 
Colombia 
Quality of hire measures how much value a new employee adds compared with what you expected when you hired them. For engineering roles, it works best as a small set of signals collected over time, such as hiring manager ratings, ramp-up milestones, performance reviews, and retention, combined into one score you track by role and hiring source.
This guide explains why quality of hire is hard to measure, gives you a simple formula, and shows which signals to track for software engineers and when. It includes check-in questions and a scorecard you can copy, example ramp-up milestones by level, the pre-hire practices that predict quality, what clients value in the senior engineers BEON.tech places, and the mistakes that make the metric misleading.
Why quality of hire matters, and why it is hard to measure
Time to hire and cost per hire tell you how efficient your process is. Quality of hire tells you whether the process works. It is the metric that connects recruiting to results, which is why talent teams keep returning to it. In LinkedIn’s Future of Recruiting 2025 report, 93% of talent acquisition professionals said accurately assessing candidates’ skills is crucial to improving quality of hire, and 61% said AI can improve how they measure it.
It is also hard to measure well. Industrial and organizational psychologists writing for SIOP point to three recurring problems: there is no standard definition, the right measures depend on the job and the company, and early signals, such as finishing a probation period, do not reliably predict long-term performance. Engineering adds its own difficulty, because individual output is hard to separate from the team’s work.
A simple quality of hire formula
The most practical approach is to pick three to five indicators, convert each to a percentage, and average them:
Quality of hire = (indicator 1 + indicator 2 + indicator 3 + …) ÷ number of indicators
For example, suppose an engineer hired six months ago has these results. This is an illustration, not a benchmark:
| Indicator | Result | Score |
|---|---|---|
| Hiring manager rating at 90 days | 4 out of 5 | 80% |
| Ramp-up milestones met on time | 9 out of 10 | 90% |
| Six-month performance review | 3 out of 4 | 75% |
| Still on the team at six months | Yes | 100% |
| Quality of hire | 86% |
The number matters less than the trend. Track the score for each role, hiring source, and interviewer panel, including agencies and staffing partners, and compare it over time. That is how you learn which channels and interview steps produce your best engineers.
What to measure for software engineers
General quality of hire guides rarely address engineering. These signals fit technical roles, and together they cover skill, impact, and fit:
| Signal | When to collect it | How to measure it | Watch out for |
|---|---|---|---|
| Hiring manager rating | 30, 90, and 180 days | A 1 to 5 rating against the expectations in the job description, plus two or three written examples. | Ratings based on impressions instead of examples. |
| Ramp-up milestones | First 90 days | Whether agreed milestones were met, such as the first merged pull request, the first feature shipped, or the first on-call shift. | Milestones that depend on access or onboarding the engineer does not control. |
| Performance review | 6 and 12 months | Your standard review, scored against the level you hired for. | Comparing engineers hired at different levels. |
| Peer and code review feedback | 90 days onward | Short structured input from teammates on code quality, collaboration, and reliability. | Turning feedback into a popularity contest. |
| Retention | 6 and 12 months | Whether the engineer is still on the team, and whether any departure was voluntary. | Counting departures caused by layoffs or reorganizations. |
Avoid activity metrics such as commit counts or lines of code. They are easy to game and say little about value. Delivery metrics like the ones popularized by DORA describe team performance, not individual performance. The SPACE framework from researchers at GitHub, Microsoft, and the University of Victoria makes the same point: developer productivity has several dimensions, including satisfaction, performance, activity, collaboration, and flow, and no single metric captures it. For more on team-level measurement, see our guide to software engineering metrics.
Example ramp-up milestones by level
Ramp-up milestones only work if you agree on them before the engineer starts. These examples are a starting point to adapt to your codebase and onboarding, not benchmarks:
| Level | By day 30 | By day 90 |
|---|---|---|
| Mid-level | Development environment set up, first small change merged, and a clear picture of how code reaches production. | Delivers well-scoped features on their own, takes part in code reviews, and handles routine bugs. |
| Senior | First meaningful change merged, and a working understanding of the architecture and its main risks. | Leads a feature end to end, reviews other engineers’ code, and proposes at least one improvement to the system or process. |
| Lead or staff | A map of the architecture, the team, and the roadmap, plus working relationships with product and design. | Owns a technical area, sets or improves a team standard, mentors others, and contributes to planning. |
When to measure quality of hire
| Timeframe | What to check |
|---|---|
| 30 days | Onboarding progress, early manager impressions, and any blockers the hiring process missed. |
| 90 days | Ramp-up milestones, a structured manager rating, and first peer feedback. |
| 6 months | Performance review, contribution to team goals, and six-month retention. |
| 12 months | Performance trend, growth in scope, and 12-month retention. This is the most reliable point to judge the hire. |
Early checkpoints help you fix onboarding problems quickly, but the 12-month view is the one to use when you judge a hiring source or change your interview process.
Quality of hire templates you can copy
Hiring manager check-in questions
Ask for a 1 to 5 rating and one concrete example for each rated question. The examples are what make the ratings comparable across managers.
At 30 days
- Is the engineer fully set up and contributing to real work? (1 to 5) What is still blocking them?
- How well does their work so far match what we expected at this level? (1 to 5) Give one example.
- Is there anything the interview process should have caught?
At 90 days
- How close is the engineer to working independently at the level we hired for? (1 to 5)
- How would you rate the quality of their code and code reviews? (1 to 5)
- How proactively do they communicate progress, blockers, and trade-offs? (1 to 5)
- Knowing what you know now, would you hire this person again? (Yes, no, or not sure)
At 6 and 12 months
- How would you rate their overall impact on the team’s goals? (1 to 5)
- How well do they understand the product and the business context of their work? (1 to 5)
- How effectively do they use AI tools while keeping quality high? (1 to 5)
- Would you hire this person again? (Yes, no, or not sure)
Quality of hire scorecard
Record each indicator, convert it to a percentage, and average the results. If one indicator matters more to you, weight it, but agree on the weights before you start collecting data.
| Indicator | When | Scale | Convert to a percentage |
|---|---|---|---|
| Hiring manager rating | 90 days | 1 to 5 | Rating divided by 5 |
| Ramp-up milestones | 90 days | Milestones met out of those planned | Share of milestones met |
| Performance review | 6 and 12 months | Your review scale | Score divided by the top of the scale |
| Would hire again | 6 and 12 months | Yes or no | Yes is 100%, no is 0% |
| Retention | 12 months | Yes or no | Yes is 100%, no is 0% |
Pre-hire signals that predict quality
Quality of hire is measured after the hire, but it is decided before it. The practices that most improve it in engineering are consistent across companies:
- A specific job description. Clear must-haves and a defined level attract the right candidates. Our job description templates for software engineers and other roles include a ready-to-use scorecard.
- Structured interviews. The same questions and criteria for every candidate make ratings comparable and easier to connect to later performance.
- A realistic work sample. A short exercise based on real work tells you more than puzzles, especially now that candidates use AI tools. See how to evaluate engineers who work with AI agents.
- A calibrated scorecard. Agree on criteria and weights before the first interview, then compare interview scores with the quality of hire score a year later.
How BEON.tech measures quality after placement
BEON.tech places senior engineers from Latin America with US companies, so the quality of each placement is also the quality of our service. Every six months, each engineer goes through a structured review with three perspectives: the client’s representative, the engineer, and a BEON.tech team member. Each one answers with concrete examples, not only ratings, across four areas:
- Commitment. Ownership of the project’s goals and staying engaged with its mission.
- Problem solving with impact. Solving complex problems through initiative, creative thinking, and high-quality execution.
- Growth. Stepping outside their comfort zone, pursuing ambitious goals, and using AI tools to improve quality or productivity.
- Team contribution. Collaboration, flexibility, and support for teammates.
The review also records recent wins, areas to improve, and goals for the next six months, so each cycle can be compared with the last and problems surface while there is still time to fix them.
What clients value in senior engineers
We reviewed the written feedback clients gave in these reviews between 2023 and 2026 to see what they mention when they describe an engineer’s best work, and where they want to see growth. A few patterns stand out:
- Shipping is what clients notice first. About two in five descriptions of an engineer’s recent wins center on features or systems they built, launched, or migrated.
- AI moved into the review. Mentions of AI were rare before 2025. In 2026, close to one in five client comments mention it, both as a win, such as adopting AI tools or shipping AI features, and as an area to grow.
- Communication is the most common growth area. About one in five growth comments ask for more proactive communication, such as raising blockers early or explaining how an update moves a milestone forward.
- Business context is a growing request. In 2026, about one in eight growth comments asked engineers to understand the product and the business better, about twice the share in 2025.
- English is rarely the issue. Fewer than one in a hundred growth comments mention English.
The lesson for any team: make communication, business context, and effective use of AI explicit in your 90-day and six-month ratings. They are what separate a good hire from a great one once the technical bar is met.
Common mistakes
- Measuring only speed and cost. A fast, cheap hire who leaves in six months is the most expensive outcome.
- Measuring too early. A 30-day rating is useful for onboarding, but it is not enough to judge a hire or a source.
- Relying on impressions. Ask for examples in every rating. It reduces bias and makes the data useful.
- Not segmenting the data. An average across all roles hides which sources and interview steps work.
- Never closing the loop. The point of the metric is to change how you hire. Review it with hiring managers at least twice a year.
How to improve quality of hire
Start by measuring a few signals consistently for the roles you hire most often. Then use the results to adjust the job description, the interview process, and your hiring sources. For many teams, the biggest improvements come from clearer requirements, structured interviews, realistic work samples, and a real onboarding plan for the first 90 days. For more on keeping good engineers after you hire them, see our guide to retaining talent in tech.
If you would rather have vetted senior engineers with this kind of follow-up built in, see how BEON.tech helps companies hire senior developers.
FAQ
What is a good quality of hire score?
There is no universal benchmark, because every company chooses different indicators and scales. A score is useful mainly as a comparison: between roles, hiring sources, interview panels, or time periods within your own company. Set a baseline with your first cohort, then aim to raise it, and investigate any source or role that consistently scores below the rest.
How do you measure quality of hire for software engineers?
Combine a few signals collected over the first year: a structured hiring manager rating at 90 days, ramp-up milestones such as the first merged pull request, performance reviews at six and 12 months, peer feedback, and retention. Convert each to a percentage, average them, and avoid activity metrics like commit counts, which say little about value.
When should you measure quality of hire?
Collect early signals at 30 and 90 days to catch onboarding problems, then measure again at six and 12 months. The 12-month point is the most reliable for judging a hire, because short-term results often do not predict long-term performance. Use the later results when you evaluate hiring sources or change your interview process.
What is the difference between quality of hire and time to hire?
Time to hire measures speed: the number of days from a candidate entering your process to accepting an offer. Quality of hire measures results: how well the person performs and whether they stay. Both matter, but optimizing for speed alone often lowers quality, so track them together and treat quality as the outcome that counts most.
