{"id":8131,"date":"2026-04-15T07:53:36","date_gmt":"2026-04-15T07:53:36","guid":{"rendered":"https:\/\/apna.co\/career-central\/?p=8131"},"modified":"2026-04-15T07:53:38","modified_gmt":"2026-04-15T07:53:38","slug":"close-multiple-job-positions-fast-apna","status":"publish","type":"post","link":"https:\/\/apna.co\/career-central\/close-multiple-job-positions-fast-apna\/","title":{"rendered":"How Employers Can Close Multiple Open Positions Quickly Using Apna"},"content":{"rendered":"\n
\"apna\"<\/figure>\n\n\n\n

The operations head at a logistics company in Gurgaon had 14 open positions last October. 6 warehouse associates<\/a>. 4 delivery coordinators<\/a>. 3 customer support executives<\/a>. 1 MIS analyst<\/a>. Festive season was 5 weeks away. Every unfilled seat was costing the company throughput. Every week of delay meant the Diwali surge would hit with a team running at 70% capacity.<\/strong> His recruiter was on 3 job portals. Had posted all 14 roles. Applications were coming in. Hundreds of them. The problem wasn’t volume. The problem was that reviewing hundreds of applications across 14 roles, screening each one, scheduling calls, chasing candidates who didn’t pick up, and coordinating interview slots with 4 different hiring managers was a full-time job for 3 people. He had 1 recruiter. Who was also handling employee documentation, onboarding for the people who’d already been hired, and answering the operations head’s “where are we on the hiring?” messages every afternoon.<\/p>\n\n\n\n

14 positions. 1 recruiter. 5 weeks. That equation doesn’t balance no matter how hard the recruiter works. Something has to give. Either the hiring quality drops because the recruiter starts shortlisting whoever’s available instead of whoever’s right. Or the timeline slips because thorough screening takes time the calendar doesn’t have. Or both.<\/p>\n\n\n\n

This is the problem that a fast hiring platform for employers is supposed to solve. Not “more applications.” Employers drowning in open positions don’t need more applications. They need the 30 right candidates surfaced from 500 wrong ones, screened before the recruiter’s day starts, and ready to interview by Thursday. That’s what closing multiple positions quickly actually requires. Not volume. Velocity with precision.<\/p>\n\n\n\n

This blog explains how that works on Apna. The specific mechanics. What happens between posting a role and filling it. And why the timeline on Apna consistently compresses to days and weeks instead of the months that traditional hiring cycles take.<\/p>\n\n\n\n

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Why Multi-Position Hiring Breaks on Traditional Platforms<\/strong><\/h2>\n\n\n\n

The standard hiring workflow on most job portals was designed for one role at a time. Post the listing. Wait for applications. Review them manually. Shortlist. Call. Schedule. Interview. Offer. That sequence works when a company is filling 1 position with a 4-week timeline. It collapses when a company needs to fill 8 or 14 or 30 positions in the same window.<\/p>\n\n\n\n

Here’s why it collapses. Every step in the sequence is serial. The recruiter reviews applications for Role 1 on Monday. Schedules calls for Role 1 on Tuesday. Reviews applications for Role 2 on Wednesday. By the time she gets to Role 5 on the following Monday, the best candidates who applied for Role 5 on the first day have already accepted offers elsewhere. They didn’t wait. They couldn’t afford to. A customer support candidate who’s actively searching usually has 2 to 3 screening calls in a week. If your call comes on day 8, someone else’s came on day 2. She went with the one that moved faster.<\/p>\n\n\n\n

Speed of response is the single most underappreciated variable in hiring. Recruiters think about “quality of hire.” They think about “culture fit.” They think about “compensation benchmarking.” Almost nobody thinks about the fact that the candidate they’re evaluating on Thursday already has an offer from the company that interviewed her on Monday. She’s not comparing your compensation package to the market. She’s comparing it to the offer letter already sitting in her inbox.<\/p>\n\n\n\n

This gets exponentially worse with multiple open positions. Each unfilled role represents lost productivity. A warehouse running 6 people short processes fewer shipments. A support team with 3 empty seats has longer response times. Every day the position stays open, the business absorbs the cost. But the traditional hiring pipeline doesn’t speed up just because the urgency is higher. It moves at the same pace regardless. Post. Wait. Review. Call. Schedule. Interview. Offer. The steps don’t compress. They queue.<\/p>\n\n\n\n

The only way to compress multiple hiring timelines simultaneously is to change the infrastructure. Not work harder within the old one. Replace the parts of it that create the queue.<\/p>\n\n\n\n

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How Apna’s Infrastructure Changes the Math<\/strong><\/h2>\n\n\n\n

Three specific things about how Apna works make multi-position hiring mechanically faster than the same process on a traditional portal. Not marginally faster. Structurally faster. The kind of faster where a role that takes 4 to 6 weeks on a legacy platform closes in 10 to 15 days.<\/p>\n\n\n\n

The first is the recruiter-first model. On most portals, the recruiter posts a listing and waits. Applications trickle in. The recruiter reviews them when there’s a critical mass. The candidate experience is: apply, wait, hope. The recruiter experience is: post, wait, review.<\/p>\n\n\n\n

On Apna, the recruiter doesn’t have to wait. She can search the candidate database directly. 60 million+ registered users. Filtered by role, skill, experience level, location, salary expectation, and work mode. A recruiter looking for customer support candidates in Bangalore with 1 to 2 years of experience and Freshdesk skills can run that search and get results in seconds. She messages candidates through the app’s chat. The candidate responds (often within hours because the notification hits their phone directly). Screening conversation happens in the chat. Interview gets scheduled. That’s the recruiter finding and reaching the candidate, not waiting for the candidate to find the listing.<\/p>\n\n\n\n

When you’re filling 14 roles, this changes everything. The recruiter isn’t waiting for 14 separate application pools to build. She’s running 14 parallel searches in the same database and reaching out to matched candidates simultaneously. Role 1 and Role 7 and Role 12 can all have candidates in screening at the same time. Not sequentially. In parallel.<\/p>\n\n\n\n

The second thing is chat-based screening. On traditional portals, the recruiter finds a promising profile, notes the phone number, calls. Candidate doesn’t pick up (this happens 40 to 60% of the time during first attempts). Recruiter calls back tomorrow. Candidate picks up but is in a meeting. Reschedule for Thursday. Thursday arrives. The call happens. 5 minutes of screening. A single screening that should take 5 minutes actually consumed 3 days of calendar time because of the phone-tag overhead.<\/p>\n\n\n\n

On Apna, the screening starts in chat. “Hi, I came across your profile for a customer support role at our company. Are you interested?” The candidate responds from their phone whenever they see it. Could be immediately. Could be 2 hours later. The conversation is asynchronous. The recruiter isn’t sitting on hold. She sends 10 messages to 10 candidates, then moves to the next role while responses come in. When they reply, she picks up the conversation. Screening happens in text in 5 minutes of actual interaction, without the 3 days of phone tag.<\/p>\n\n\n\n

Multiply that efficiency across 14 roles and the time savings are enormous. 14 roles, 10 candidates each, all being screened through chat simultaneously. A recruiter who’d need 3 weeks to do this through phone calls can do it in 3 to 4 days through chat because the asynchronous model eliminates the waiting.<\/p>\n\n\n\n

The third thing is candidate reach. Traditional portals concentrate their user base in metro cities. Bangalore, Mumbai, Delhi, Hyderabad, Pune. A company posting a role in Jaipur or Indore or Lucknow or Coimbatore gets a thinner applicant pool. Fewer applications. Fewer qualified matches. The hiring timeline stretches because the supply side is thin.<\/p>\n\n\n\n

Apna’s user base spans over 900 cities and 40% of India’s pincodes. The platform’s Tier-2 and Tier-3 city coverage is deeper than any other major job platform in India. A company in Pune posting a remote customer support role sees candidates from Indore, Raipur, Bhopal, Jaipur, Nagpur, Coimbatore. That geographic breadth means the candidate pool is larger for every listing. Larger pool means more qualified matches. More matches means faster shortlisting. Faster shortlisting means faster hiring.<\/p>\n\n\n\n

For companies doing multi-city hiring, this is the structural advantage that matters most. A retail chain opening 5 stores across 5 different cities doesn’t need to use 5 different local hiring strategies. One platform. One posting per role. Candidates from all 5 cities in the same search.<\/p>\n\n\n\n

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The AI Layer That Didn’t Exist 2 Years Ago<\/strong><\/h2>\n\n\n\n

Everything above, the recruiter-first search, the chat-based screening, the geographic reach, existed on Apna before AI entered the picture. What AI added is the layer that made all of it work at the speed that multi-position hiring actually requires.<\/p>\n\n\n\n

When a recruiter posts a role, Apna’s AI matching algorithm immediately scans the candidate database and surfaces the most relevant profiles. Not keyword matching from 2015 where “customer support” matched “customer support” and missed “client servicing” and “helpdesk associate.” Semantic matching trained on millions of successful hires that understands functional equivalence. The algorithm knows which candidates are most likely to be a good fit based on what’s worked for similar roles in the past. The recruiter opens her dashboard and sees AI-recommended candidates already sorted by relevance. She didn’t search for them. The system found them for her.<\/p>\n\n\n\n

For a recruiter managing 14 open roles, this is the difference between drowning and functioning. She’s not running 14 manual searches. The AI is running them continuously, updating recommendations as new candidates register and new applications come in. Her job shifts from “find the candidates” to “review the candidates the system found.”<\/p>\n\n\n\n

Then there’s the piece that most changes the timeline for volume hiring: the AI Calling Agent.<\/p>\n\n\n\n

Built on Apna’s proprietary agentic AI stack, the AI Calling Agent does something that no amount of recruiter productivity improvement can replicate. It calls candidates. Automatically. In English, Hindi, or regional languages. The moment a job is posted.<\/p>\n\n\n\n

The AI calls matched candidates, introduces the role, asks screening questions configured by the recruiter (“Are you comfortable with night shifts?” “What’s your current notice period?” “Do you have experience with Freshdesk?”), evaluates the responses through voice analytics, and auto-shortlists the candidates who meet the criteria. It runs 24\/7. It can handle over 10,000 simultaneous conversations. Its candidate connection rate is above 80%, compared to the roughly 30% that human recruiters achieve on cold calls.<\/p>\n\n\n\n

For the Gurgaon logistics company from the opening of this blog, here’s what this means in practice. Monday morning: recruiter posts all 14 roles on Apna. Monday afternoon: AI has already matched candidates from the database to each role and the AI Calling Agent has started screening calls. Tuesday morning: the recruiter opens her dashboard and sees, for each of the 14 roles, a list of candidates who’ve been contacted, screened, and sorted. She didn’t make a single phone call. She reviews the pre-screened lists. Shortlists her top picks. Coordinates with the 4 hiring managers. Interviews happen Wednesday through Friday. First offers go out the following Monday.<\/p>\n\n\n\n

14 roles. Posted to screened shortlist in 24 hours. First offers in 10 days. With 1 recruiter. Not because the recruiter worked 18-hour days. Because the infrastructure did the work that used to require a team of 3.<\/p>\n\n\n\n

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What This Looks Like for Real Companies<\/strong><\/h2>\n\n\n\n

The theory is clean. The reality of multi-position hiring is always messier. Candidates drop out. Hiring managers reschedule. Offer negotiations stall. The best candidate takes a competing offer because the internal approval process took 4 days too long. A fast hiring platform for employers doesn’t eliminate these problems. It reduces the surface area where each problem can do damage.<\/p>\n\n\n\n

When the candidate pipeline fills faster, losing 1 candidate to a competing offer doesn’t reset the timeline by 2 weeks. There’s already a second and third option in the screened pool. When screening happens through AI calls instead of manual phone tag, the 3-day phone-tag delay disappears. When the recruiter can search the database and message candidates directly instead of waiting for applications, the slowest part of traditional hiring (waiting for the right people to find your listing) gets replaced by the recruiter going and finding them.<\/p>\n\n\n\n

The compounding effect matters more than any individual feature. Chat screening is maybe 2 days faster than phone screening for a single role. AI matching saves maybe 3 hours of manual profile review. The recruiter-first search model saves maybe 2 days of waiting for applications to build. Individually, each one is a modest improvement. Combined across 14 simultaneous roles, the aggregate time savings is weeks. Not days. Weeks.<\/p>\n\n\n\n

And there’s an economic argument that doesn’t get discussed enough. Every day a position stays unfilled has a cost. A warehouse associate position vacant for 30 days means 30 days of reduced throughput. A customer support seat empty for 3 weeks means 3 weeks of longer queue times and lower satisfaction scores. A delivery coordinator position unfilled during festive season means missed deliveries and unhappy customers during the highest-revenue period of the year. The cost of slow hiring isn’t just recruiter time. It’s business output.<\/p>\n\n\n\n

Companies that track cost-per-vacant-day (and more should) find that reducing time-to-fill from 45 days to 15 days doesn’t just save recruiter effort. It saves the revenue that was being lost every day the seat was empty. For a company with 14 open positions, compressing the hiring timeline by 3 weeks across all 14 roles recovers weeks of productivity that would have been lost to understaffing. That recovery dwarfs the cost of using the platform.<\/p>\n\n\n\n

The Gurgaon logistics company filled 11 of its 14 positions within 3 weeks. The remaining 3 (including the MIS analyst, a more specialised role) took another 10 days. Festive season started with the team at 96% capacity instead of the 70% they were projecting when the hiring sprint began. The operations head stopped sending the daily “where are we on hiring?” messages around week 2. Because the dashboard showed him exactly where they were. In real time. Without anyone having to compile a status update.<\/p>\n\n\n\n

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The question employers ask when evaluating a fast hiring platform isn’t “does it have AI?” Every platform claims AI in 2026. The question that actually matters is: “if I post 10 roles today, how many of them will have screened, qualified candidates in my interview pipeline by end of this week?”<\/p>\n\n\n\n

On a traditional portal, the honest answer is maybe 2 or 3. Because the application pool takes days to build, manual screening takes days per role, and phone-tag scheduling adds days on top of that.<\/p>\n\n\n\n

On Apna, the answer is closer to 8 or 9. Because the AI matches candidates from a 60 million+ database the moment the role goes live. The AI Calling Agent screens them overnight. The recruiter-first model lets the recruiter directly reach candidates who match but haven’t applied yet. And the chat-based interaction eliminates the dead time between “interested candidate” and “scheduled interview.”<\/p>\n\n\n\n

That’s not a feature comparison. That’s a timeline comparison. And for a company with 14 open seats and a hiring manager asking every afternoon “where are we?”, the timeline is the only number that matters.<\/p>\n\n\n\n

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FAQs<\/strong> About Bulk Hiring on Apna<\/strong><\/h2>\n\n\n\n

What makes Apna a fast hiring platform for employers?<\/strong> Three things working together: AI-powered candidate matching that surfaces relevant profiles the moment a role is posted, a recruiter-first model that lets employers search and message candidates directly instead of waiting for applications, and chat-based screening that eliminates the days of phone tag that traditional hiring requires. The AI Calling Agent adds a fourth layer for volume hiring, automatically screening candidates by voice and delivering a pre-sorted shortlist to the recruiter’s dashboard.<\/p>\n\n\n\n

How quickly can an employer start receiving qualified candidates?<\/strong> Within hours of posting. The AI matching begins immediately, scanning 60 million+ profiles against the job requirements. For roles using the AI Calling Agent, screened and sorted candidates can appear on the recruiter’s dashboard by the next morning. The recruiter can also run parallel searches in the database and start messaging matched candidates on the same day the role is posted.<\/p>\n\n\n\n

Does this work for hiring across multiple cities?<\/strong> Yes. Apna’s user base covers 900+ cities and 40% of India’s pincodes. A company posting a remote role or a multi-city hiring drive sees candidates from Tier-1, Tier-2, and Tier-3 cities in the same search. This is particularly useful for retail, logistics, and customer support hiring where positions need to be filled across multiple locations simultaneously.<\/p>\n\n\n\n

Is this only useful for entry-level or blue-collar hiring?<\/strong> The AI matching and recruiter-first search work across all role levels. The AI Calling Agent is most impactful for high-volume hiring (customer support, logistics, retail, BPO, warehouse operations) where screening criteria are definable and speed matters most. For mid-level and specialised roles, the platform’s database search and chat-based screening still significantly compress the hiring timeline compared to traditional portals.<\/p>\n\n\n\n

How does the AI Calling Agent actually work?<\/strong> It’s an automated voice screening tool built on Apna’s agentic AI stack. When a role is posted, it calls matched candidates in English, Hindi, or regional languages. It introduces the role, asks recruiter-configured screening questions, evaluates responses through voice analytics, and auto-shortlists qualifying candidates. It operates 24\/7, handles 10,000+ simultaneous conversations, and achieves an 80%+ connection rate compared to the 30% average for manual recruiter calls.<\/p>\n\n\n\n

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All the Best!<\/em><\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"

The operations head at a logistics company in Gurgaon had 14 open positions last October. 6 warehouse associates. 4 delivery coordinators. 3 customer support executives. 1 MIS analyst. Festive season was 5 weeks away. Every unfilled seat was costing the company throughput. Every week of delay meant the Diwali surge would hit with a team […]<\/p>\n","protected":false},"author":5,"featured_media":4138,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[23],"tags":[],"class_list":{"0":"post-8131","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-apnaindia"},"yoast_head":"\nHow Employers Can Close Multiple Job Positions Fast Using Apna<\/title>\n<meta name=\"description\" content=\"Need to hire for multiple roles fast? 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