Live opening · Posted 3 days ago

Talent Acquisition Specialist

HCLTech · Noida, Uttar Pradesh, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 3 days ago
CompanyHCLTech
LocationNoida, Uttar Pradesh, India (On-site)
Work modeNo
SkillsTalent Acquisition, Kubernetes
SourceLinkedin
ListedPosted 3 days ago

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About the role

Description supplied by the original job listing.

Location: Noida
Job Summary
We are searching for a high-impact Talent Acquisition Specialist with a strong IT Product / AI hiring mindset. This role goes beyond traditional sourcing and execution. We are seeking a Talent Advisor who can influence hiring decisions using market insights, engage senior AI and engineering talent, and act as a trusted partner to business and HR leadership.
Key Responsibilities
1. End-to-End Recruitment Ownership
Manage full-cycle recruitment for niche and senior-level roles.
Drive hiring from JD intake to joining, ensuring speed, quality, and an excellent candidate experience.
2. Quality-Driven Talent Sourcing
Consistently identify and engage top-quality talent across Data & AI, AI Architecture, AI Research, AI Engineering, Product Management, Machine Learning, Ecosystem Partnerships, and cloud-native AI talent with expertise in leading cloud AI platforms, Generative AI, LLMs, data platforms, and modern MLOps ecosystems.
Use mainstream sourcing channels effectively: LinkedIn Recruiter, job portals, networking, and employee referrals.
Demonstrate hands-on experience and curiosity to explore non-traditional sourcing channels, including GitHub, Stack Overflow, and LLM / AI-based candidate search tools.
Continuously experiment with new sourcing approaches to improve talent quality and pipeline health.
3. Talent Market Insights & Advisory
Conduct in-depth talent intelligence research on skill availability, talent geography, compensation benchmarks, and competitor hiring patterns.
Use insights to influence Hiring Managers and Leaders and recommend JD refinements based on market realities.
Develop a strong understanding of emerging AI and cloud technology trends, particularly within the enterprise AI ecosystem, including Generative AI, LLMs, MLOps, data platforms, and cloud AI services, to assess talent availability and advise hiring leaders.
Build credibility as a Talent Advisor, not just an execution partner.
4. Senior Talent Engagement & Influence
Confidently engage with senior and niche technical talent.
Effectively pitch HCLTech's AI vision, growth opportunities, cloud and GenAI initiatives, and business impact, including strategic programs leveraging AI technologies and modern data platforms.
Build long-term relationships with passive candidates.
5. Offer Management & Negotiation
Lead offer discussions and negotiations with candidates.
Partner with HR and Hiring Leaders to justify salary proposals using market data, benchmarks, and candidate value, and secure timely approvals without compromising talent quality.
Ensure win-win outcomes for both HCLTech and candidates.
6. Candidate Engagement & Joiner Conversion
Own the post-offer engagement strategy, including structured candidate engagement plans and strong alignment and engagement throughout the notice period.
Proactively ensure Hiring Leaders connect with offered candidates.
Deliver a 95%+ offer-to-join conversion ratio.
7. ATS & Compliance Excellence
Work extensively with the Applicant Tracking System (ATS).
Ensure 100% recruitment process compliance through the ATS.
Required Skills & Experience
4 to 9 years of IT full-cycle recruitment experience.
Strong communication, stakeholder management, and influencing skills.
Mandatory experience in AI / Data & AI hiring, with exposure to hiring talent across AI, Data Engineering, Machine Learning, MLOps, Generative AI, and Cloud Architecture roles.
Ability to operate as a trusted Talent Advisor to Hiring Managers and Leaders.
Preferred Technical Awareness
Familiarity with leading AI and cloud technology stacks, including major cloud AI platforms, Generative AI and LLM frameworks, data engineering platforms, MLOps tools, and container technologies such as Kubernetes, enabling deeper talent conversations and market intelligence discussions.

Work arrangement
No

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