About Lyzr

Lyzr is a Series A–backed enterprise AI company building a full-stack agent infrastructure platform that helps organizations design, deploy, and govern AI agents. Our platform enables enterprises to move beyond isolated AI use cases and into reliable, production-grade agentic workflows with strong controls around security, accuracy, and compliance.

Recognized by Accenture and Harvard Business School–led innovation ecosystems, Lyzr works with global enterprises to reimagine complex workflows using agentic AI. We focus on making AI agents dependable at scale - so teams can replace fragmented tool stacks with a unified, governed intelligence layer.

About The Role

We don’t believe People is support. We believe People is strategy.

As a People Ops Intern, you will build the systems that shape how we hire, onboard, and grow talent.

You won’t “assist.” You’ll help design how a company scales its culture.

If you’re someone who wants to understand how high-performing teams are built from scratch — this is your front-row seat.

What You’ll Own

Hiring & Talent Ops

• Coordinate interviews across teams and time zones

• Drive candidate communication end-to-end

• Maintain ATS hygiene and hiring dashboards

• Support sourcing experiments and outreach campaigns

• Help improve candidate experience workflows

Onboarding & People Systems

• Build structured onboarding journeys

• Create documentation that scales clarity

• Ensure Day 0 → Day 30 experience is seamless

• Partner with founders to streamline processes

Culture & Engagement

• Support team rituals and engagement initiatives

• Help run feedback loops and pulse check systems

• Assist in building internal knowledge systems

Who This Is For

• Final-year student or recent graduate

• Deeply organised and detail-obsessed

• Strong written communicator

• High ownership mindset

• Curious about startups and high-performance cultures

• Comfortable working in ambiguity

You’ll thrive here if:

• You move fast but don’t drop details

• You care about people experience

• You think in systems, not tasks

• You want exposure, not supervision