Talent Acquisition Specialist
2 days ago
Talent Acquisition Manager (AI-First Recruiting)
Location:
Bengaluru (hybrid)
Experience:
2–4 years |
Function:
Talent Acquisition (Technical)
Type:
Full-time |
Role:
Individual contributor (with scope to lead as team scales)
Why this role
Help us hire engineers and other technical roles
by operating and configuring our AI recruiter (Fabric)
. Instead of running a traditional, manual-heavy process, you'll translate role requirements into
AI configurations, prompts, rubrics, and thresholds
so the tool can source, screen, interview, and prioritize candidates faster—with you owning quality and outcomes.
What you'll do
- Turn JDs into AI configs:
Break down role requirements (skills, seniority, signals, red flags) into structured inputs, weights, and scoring rules for Fabric. - Calibrate the model for each role:
Provide few-shot examples, define knockout criteria, tune pass thresholds, and iterate until shortlists match hiring-manager expectations. - Run AI-first pipelines end-to-end:
Launch roles, monitor dashboards, review AI interview summaries, spot-check edge cases, and move high-signal candidates to final rounds. - Quality & fairness oversight:
Investigate false positives/negatives, refine prompts, and maintain consistent, bias-aware evaluation rubrics. - Cheating detection supervision:
Review AI flags, validate evidence, and adjust policies to keep signal clean. - Sourcing via platforms (as needed):
Use
LinkedIn Recruiter
and
Naukri Recruiter
to top up the funnel; feed sourced profiles back into Fabric for consistent evaluation. - Partner with hiring managers:
Run quick role-intake sessions, align on success criteria, and deliver weekly hiring readouts with clear next actions. - Measure and improve:
Track time-to-first-screen, shortlist precision/recall, onsite-to-offer, source effectiveness; run small experiments to improve conversion.
What success looks like (first 90 days)
- Intake-to-first shortlist in
≤48 hours
for priority roles. - ≥80%
of applicants screened end-to-end by AI with your calibrated rubric. - Shortlist quality that hiring managers rate
≥8/10
on relevance. - A simple playbook for repeating configurations across similar roles.
You'll thrive if you have
- 2–4 years
in
technical recruiting
(e.g., Backend/Frontend/Full-stack, Data/ML, QA, DevOps/SRE, Platform), with clear closures you can speak to. - Hands-on with
LinkedIn Recruiter
and
Naukri Recruiter
(projects, advanced Boolean, talent mapping)—comfortable sourcing when needed. - Strong grasp of how to
assess engineering roles
(signals in resumes/portfolios, what good looks like at 0–3/3–5/5–8 years, common pitfalls). - Product mindset
and clear writing: you can turn messy requirements into crisp prompts, rules, and checklists. - Data literacy:
comfortable reading dashboards, comparing cohorts, and making changes based on evidence. - Startup experience
and bias for speed; Bangalore market exposure is a plus.
Nice to have
- Familiarity with ATS/CRM workflows and clean documentation habits.
- Basics of
JSON/Google Sheets
; light SQL is a plus. - Experience running structured interviews or building scorecards.
What we offer
- A front-row seat to AI-driven recruiting, with real ownership of outcomes.
- Direct access to founders and product; your feedback ships.
- Competitive salary with growth path into Lead/Head of TA (AI Ops).
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