Senior Talent Acquisition Partner

Vista Equity Partners is a leading global investment firm focused exclusively on enterprise software, data, and technology-enabled businesses. With over $100B in assets under management and a portfolio of 90+ software product companies worldwide, Vista accelerates growth through operational excellence, shared expertise, and long-term partnership. In India, Vista’s presence continues to expand with 45+ portfolio companies employing more than 17,000 professionals across technology, product, customer success, and operations — reinforcing India’s strategic role as a hub of innovation and talent within the Vista ecosystem.

Through its Agentic AI Factory, Vista is embedding Generative AI across its global portfolio — enabling companies to integrate intelligent, responsible AI into products, operations, and decision-making. This initiative is strengthened through portfolio-wide learning programs, leadership workshops, and AI hackathons that foster innovation, build fluency, and accelerate practical AI adoption across teams.

Amtech is a leading provider of enterprise software solutions for the packaging, printing, and manufacturing industries. Our integrated systems streamline order management, production planning, scheduling, inventory, and business analytics — empowering customers to drive efficiency, reduce costs, and improve operational performance. With a strong commitment to innovation and customer success, Amtech delivers reliable technology backed by deep industry expertise.

With Vista’s investment and strategic guidance, we combine the agility of a growing technology organization with the scale, stability, and career mobility of a global software ecosystem.

The Senior Talent Acquisition Partner will manage end-to-end recruitment activities, supporting hiring needs across the organization through effective sourcing, screening, stakeholder coordination, and offer management. The role will use recruitment analytics to track hiring progress and improve outcomes, while also managing vendor relationships, employee referral channels, and internal sourcing efforts. The ideal candidate will bring 3-6 years of recruitment experience and a willingness to upskill and use AI tools efficiently to improve hiring productivity and candidate engagement.

• Hiring requirements are managed efficiently across assigned roles, with timely progress updates, clear stakeholder communication, and strong follow-through.
• Quality candidate pipelines are built through a balanced sourcing approach, including internal sourcing, employee referrals, vendor channels, direct outreach, and AI-assisted sourcing methods.
• AI tools are effectively used at different stages of talent acquisition to improve productivity, sourcing accuracy, market research, candidate communication, and workflow efficiency.
• Recruitment analytics are used to monitor hiring progress, identify bottlenecks, evaluate sourcing effectiveness, and support data-informed hiring decisions.
• Vendor performance is coordinated and tracked to ensure timely, relevant, and quality candidate submissions.
• Candidate and hiring manager experience is maintained through structured communication, timely follow-ups, and process discipline.
• Recruitment data, dashboards, and status updates are accurate, current, and useful for decision-making.

• →Manage end-to-end recruitment activities, including sourcing, screening, interview coordination, offer support, stakeholder updates, and closure.
• →Partner with hiring managers and People & Culture stakeholders to understand role requirements, hiring priorities, success profiles, and market realities.
• →Use AI-enabled tools to support talent mapping, Boolean search refinement, candidate identification, market research, job description calibration, and sourcing strategy.
• →Build relevant candidate pipelines through internal sourcing, employee referrals, direct outreach, vendor channels, and AI-assisted search techniques.
• →Screen candidates effectively using structured assessment criteria, role requirements, and AI-supported productivity tools where appropriate.
• →Create and personalize candidate communication using AI tools while ensuring communication remains accurate, professional, human, and aligned with company tone.
• →Coordinate with recruitment vendors and track vendor submissions, candidate quality, turnaround time, and conversion effectiveness.
• →Use recruitment analytics to monitor hiring progress, track funnel metrics, identify process bottlenecks, and recommend corrective actions.
• →Maintain accurate recruitment data, candidate status updates, interview feedback tracking, and process documentation in the ATS and related systems.
• →Continuously identify opportunities to improve TA workflows through automation, AI adoption, better reporting, and process discipline.
• →Ensure responsible use of AI tools by maintaining confidentiality, data privacy, accuracy, and human judgment in recruitment decisions.
• →Maintain a positive candidate and hiring manager experience through proactive communication, timely follow-ups, and structured process management.

Technical Expectations

• Applicant Tracking System (ATS) tools for managing candidate pipelines, recruitment stages, hiring records, and recruitment workflows.
• Experience with Greenhouse will be an added advantage.
• Exposure to relevant AI tools and use them efficiently to improve sourcing, candidate engagement, and recruitment workflow productivity.
• 3- 7 years of relevant experience in end-to-end recruitment.

AI Proficiency Expectations: 

The candidate must demonstrate practical proficiency in using AI tools across the recruitment lifecycle, including:

• Role Understanding and Intake: Using AI to support job description refinement, competency mapping, market benchmarking, and hiring manager discussion preparation.
• Sourcing and Talent Mapping: Using AI-assisted search techniques to improve Boolean strings, identify adjacent talent pools, map companies, and generate sourcing strategies.
• Candidate Screening: Using AI tools to improve screening productivity, summarize candidate profiles, compare resumes against role requirements, and prepare structured screening notes.
• Candidate Engagement: Using AI to draft and personalize outreach messages, follow-ups, interview reminders, and candidate communication while maintaining a human and professional tone.
• Recruitment Analytics: Using AI and reporting tools to analyze hiring funnel data, identify bottlenecks, interpret sourcing effectiveness, and prepare stakeholder updates.
• Workflow Productivity: Using AI to improve day-to-day efficiency in documentation, interview summaries, status reporting, meeting preparation, and recruitment process tracking.
• Responsible AI Usage: Applying AI ethically and responsibly, ensuring confidentiality, accuracy, bias awareness, and human validation before decisions or communication are finalized.