Placement Success Lead

NXTWAVE

Placement Success Lead

Academy, Intensive, NIAT

Location

Hyderabad (In-Office)

Employment Type

Full-Time

Work Schedule

6 days a week, 9:30 AM – 6:30 PM, with 1st & 3rd Saturday off

Openings

5 (1 - Academy, 1 - Intensive, 3 - NIAT)

About NxtWave

NxtWave is one of Indias fastest-growing ed-tech startups, reshaping the tech education landscape by bridging the gap between industry needs and student readiness. With prestigious recognitions such as Technology Pioneer 2024 by the World Economic Forum and Forbes India 30 Under 30, NxtWaves impact continues to grow rapidly across India.

About the Role

Every year, NxtWave prepares thousands of students to become software engineers — but preparation only counts if it converts into an actual offer. Somewhere between assessment-qualified and hired is a gap that no curriculum update alone can close: the right student needs to be matched to the right opportunity, coached through a hiring process that shifts every quarter, and given a real shot when its on the line. That gap is yours to close.

Youll own placement outcomes for one product/program end-to-end — not as a support function to the Placement Partnership team (CRMs), but as the person deciding who gets shortlisted, how theyre prepped, why they got rejected, and what needs to change next. The hiring opportunities you work with, and the curriculum your students come from, are Software Engineering roles — SDE, full stack, backend, and beyond. Youll need to actually understand the code your students are being tested on, not just the process around it.

Hiring itself is changing fast in the AI era — interview formats, assignments, and skill bars are all shifting under AIs influence. Youll need to notice that shift before it shows up in your placement numbers, and use AI yourself to keep your team ahead of it rather than reacting to it.

Key Responsibilities

• Candidate Shortlisting: Own the shortlisting process for your program/product — matching students to software engineering hiring opportunities based on resume quality, technical skills, assessment performance, mock interview performance, and company-specific eligibility criteria.
• Candidate Preparation & Mentorship: Drive assessment prep, assignment guidance, interview prep, company-specific mentoring, and last-minute doubt resolution for shortlisted students across every stage of the hiring process.
• Rejection Selection Analysis (RSA): Own the post-process analysis loop for your program/product — capture reasons for selection/rejection, stage-wise elimination, and skill gaps, and turn findings into curriculum, assessment, and process changes, not just a report.
• Hiring Intelligence: Continuously gather intelligence on interview questions, assessment patterns, coding problems, assignment trends, and company/industry expectations; convert this into better prep resources and mentoring strategies before your students walk in, not after they walk out.
• AI-Driven Process Improvement: Use AI tools to improve how the team works — automating parts of shortlisting and reporting, generating and personalizing prep content, running AI-based mock interviews, and speeding up RSA analysis — rather than only running these processes manually.
• Team Leadership: Build, manage, and coach a team (Technical Mentors) of 8–10 members with clear weekly KPIs tied to placement outcomes, not just activity volume.
• Cross-Functional Collaboration: Work closely with Partnership Partnership, Placement Operations, Assessment, and Curriculum teams to close the loop between hiring intelligence/RSA insights and actual improvements in student outcomes.

Key Outcomes

• Hiring Positions Filled: Maximize the number of open hiring positions filled by students in your program/product.
• Placement Rate of Assessment-Qualified Students: Improve the placement rate of students who have qualified the internal assessment criteria for your program/product.
• RSA-Driven Improvements: Convert rejection analysis into a defined number of actionable improvements each week across curriculum, assessments, or prep processes.
• Hiring Intelligence Repository: Maintain a live, actionable repository of hiring intelligence for your program/product that feeds curriculum, assessment, and mentoring updates.
• Team Performance: Run a high-performing team of 8–10 with clear weekly KPIs on shortlisting throughput, mentoring coverage, and prep-to-placement conversion.

Non-Negotiables

• 5+ years of overall experience with programming and software development background — comfortable evaluating code, DSA, and technical assessments, since every opportunity and curriculum is Software Engineering-focused.
• Experience managing or closely leading a team of 3–5 members on similar operating systems.

You Might Be a Good Fit If

• You can look at a rejected candidates interview feedback and immediately see three things that should change — not just for that student, but for the whole cohort.
• Youve run structured, data-led shortlisting before, and you get uncomfortable when a placement process runs on gut feel instead of signal.
• Youve turned hiring intelligence — interview patterns, coding trends, company expectations — into real changes in how students get prepared, not a slide that gets forgotten after the debrief.
• You notice hiring bars shifting before anyone else does, and youre already rebuilding your playbook around it rather than waiting for someone to tell you AI changed the rules.
• You use AI as part of how you work, not just how you talk about work — youd rather rebuild your teams shortlisting or prep process around it than bolt it on as an extra step.
• You can influence other related teams without direct authority, because you make people want to act on what you found rather than just agree with it in the room.
• Youre comfortable being judged on outcomes — positions filled, placement rate — not on how many activities you have done.

Strong Candidates May Also Have

• Prior experience in ed-tech, campus placements, or talent acquisition.
• Familiarity with technical hiring processes (coding assessments, technical interviews) relevant to software/tech roles.

What Makes This Role Exciting

• You get to own outcomes for real peoples careers, not a project or a dashboard — every positions filled number is someones first job, some family uplifted.
• Youre building the placement playbook as hiring itself is being rewritten by AI — get it right here and it becomes how every other program runs placements.