Lakshya

Legal, Finance & People

Technical Recruiter

Business · the pipeline

The function everyone underestimates until they try to hire twelve engineers in a quarter.

The function everyone underestimates until they try to hire twelve engineers in a quarter.

A day that is actually representative

TimeWhat you are actually doing
09:00Sourcing. The candidates worth hiring are not applying, which is the whole job.
10:30Screening calls where the skill is assessing without pretending to be technical.
13:00A calibration with a hiring manager whose bar is real but unwritten.
15:00Closing — where offers are won and lost, and where most recruiters are weakest.
16:30Funnel data. Where candidates drop is a diagnosis of your own process.

The decisive round

“You've had a role open for four months.”

Interviewer: “Nine candidates rejected at the final round. What's happening?”

A weak answer. “I'd source more candidates and widen the search criteria to build a bigger pipeline, and work with the hiring manager to make sure we're moving quickly on strong candidates.” Adds volume to a process failing at the last stage. Nine rejections at final round means the top of the funnel is working and something after it is not.

A strong answer. “Nine at final round is actually good news about my sourcing and bad news about everything else, so pouring more candidates in would be the wrong fix and an expensive one — it costs those candidates their time too.

There are only about three causes. The bar is genuinely higher than the role as written, which means the job description and the compensation band are for a different job than the one being interviewed for. The panel is inconsistent — different interviewers testing different things and one person effectively holding a veto. Or the hiring manager doesn't actually want to hire, which happens more than people admit, usually because they have someone internal in mind or they're unsure about the headcount.

So I'd read the scorecards for all nine, side by side. That's the diagnosis. If the rejections cluster on one interviewer, it's a panel problem. If they cluster on a skill not in the job description, it's a definition problem. If the feedback is vague across the board — 'not quite the level' — that's the third cause and it's the hardest conversation.

Then I'd have that conversation directly with the hiring manager: 'We've now spent about sixty candidate-hours and forty of the panel's. I don't think the problem is supply. Can we write down what a hire looks like, specifically enough that I could recognise one?' Frequently that exercise itself resolves it.

And I'd check the market. If the band is at the 40th percentile for the skill, the strong candidates are declining before the final round and I'm only seeing the ones who couldn't get better offers.”

Diagnosing at the failing stage rather than adding volume, reading scorecards side by side, and naming the possibility that the hiring manager isn't committed. Counting candidate-hours is what makes the conversation land.

What to build or bring

  • Your funnel numbers — sourced to screened to onsite to offer to accept.
  • A hard role you filled, and where the person came from.
  • Your offer-accept rate, which is where recruiters differentiate most.
  • Enough technical literacy to have a real conversation with an engineer. This is the single biggest gap in the market.

Compensation

MarketBandNotes
United States$90k – $160kOften with a placement-linked component
India₹8L – ₹28LVery large market; strong at GCCs during scale-up

The book for this field

Legal, Finance & People

Business functions inside a technology company: commercial counsel and legal operations, technology finance and SaaS metrics, recruiting and people operations — and why all three are now systems-building jobs.

CHAPTER 4Recruiting and people operationsTechnical recruiting is the largest people title here, and it is measured like a funnel.READ THE CHAPTER →CHAPTER 1Business functions inside a technology company632 postings. Scaling in 93%, data and analytics in 91%, AI in 84% — these are not generic corporate roles.READ THE CHAPTER →CHAPTER 3Finance in a technology businessSaaS metrics, revenue recognition, and why the finance analyst is expected to write SQL.READ THE CHAPTER →

All 4 chapters in Legal, Finance & People →

Cross-cutting

Skills every archetype tests

These are shared across every field on this site — the same question asked in different vocabulary — so preparation here compounds rather than being spent once. The book above is specific to your field.

Measuring what resists measurementTested in every field on this site under a different name — evals, SLOs, DORA, ablations. Named in 59% of AI and 42% of platform postings, and almost nobody studies it deliberately.READ THE CHAPTER →Discovery before solutionThe decisive round in three separate archetypes, with the lowest pass rate of any stage.READ THE CHAPTER →The controlOne habit separates strong candidates from plausible ones more reliably than any technical depth.READ THE CHAPTER →

Practice the 10 Business questions →  ·  Back to Legal, Finance & People →