Agentic Systems Engineer Intern (Summer 2026)

Our Mission

At Phygtl, we are solving the problem of student social isolation — a challenge affecting 60%+ of today’s students, contributing to rising depression and anxiety.
We build technology that can reduce isolation by up to 40%, by helping students form real campus connections through shared real-world moments — bridging the physical and digital worlds.

Who We Are

Headquartered in San Francisco, our team includes PhDs from Stanford, UC Berkeley, MIT, and Carnegie Mellon, alongside builders from Niantic, Meta, Magic Leap, Riot Games, Ubisoft, and Zynga. Led by a Silicon Valley-based serial entrepreneur, we’re united by a mission to rescue next-gen from Social Atrophy.

Our Moat

Phygtl builds systems that help students meet and build identity in real life. Vyry is a context-aware initiation engine where quests end in physical action. Retention is earned through participation — not notifications.

The Role

• You’ll join the team building Vyry, a mobile app that helps students meet in real life through short, coordinated campus quests.
• Right now, our focus is Quest Participation optimization: keeping peers on the quest screen while they coordinate via chat, voice, and AR Meet, without state glitches, drop-offs, or broken realtime behavior.
• This role is not about “building chatbots.”
  It’s about shipping realtime intelligence inside a live social product, where state correctness, latency, and user trust matter.

What You’ll Work On

• Designing context-aware quest logic (physical + social + temporal signals)
• Detecting stall or drop-off conditions during coordination
• Suggesting structured micro-actions that increase completion probability
• Instrumenting evaluation loops tied to measurable behavioral outcomes
• Shipping production-facing components

You will operate on top of existing real-time systems — not rebuild infrastructure.

What We’re Looking For

You are:

• A strong computer science or engineering student
• Someone who has shipped real systems (GitHub required)
• Comfortable reasoning about state transitions and edge cases
• Curious about AI systems beyond simple prompt usage
• Able to move from idea → working prototype quickly

You should be able to:

• Design a simple state-aware workflow
• Think through failure modes
• Explain tradeoffs (latency, cost, reliability)
• Tie technical decisions to measurable outcomes

Bonus if you’ve built:

• Agentic workflows
• Multiplayer or event-driven systems
• Evaluation pipelines for AI systems
• Side projects used by real users

How We Evaluate

We prioritize:

• Systems clarity (state + failure thinking)
• Execution speed
• Ownership
• Depth over pedigree

Why Join Phygtl

Work on a Real Behavioral Problem. You won’t optimize clicks. You’ll design systems that influence real-world human coordination and identity formation.

This is AI applied to physical behavior — not interface optimization.

Ship Systems That Matter

Your work will tie directly to:

• IRL Quest Completion Rate
• D30 Retention

You won’t build experiments that disappear. You’ll ship components used by live campus communities.

Learn From Operators Who’ve Built at Scale

You’ll work with the foundering team, engineers and researchers from:

• Founder DNA
• Roblox (LLM + search systems)
• Niantic (AR + real-world coordination)
• Stanford / Berkeley / MIT / CMU

Expect depth, not hand-holding.

Operate in a High-Bar, Low-Bureaucracy Environment

We value:

• Meritocracy over pedigree
• Shipped systems over slide decks
• Clear thinking over buzzwords

Ownership comes early. Responsibility scales with performance.

Build a Rare Skill Set

You’ll gain experience at the intersection of:

• Agentic AI systems
• Real-time coordination
• Behavioral metrics
• Spatial computing

Few internships operate at this boundary.

Compensation & Structure

• Competitive compensation
• Flexible remote structure
• FT 3 months or PT 6 months
• High ownership, small team

Apply

Send a single PDF including:

• CV
• GitHub
• A concise architecture walkthrough of one system you built
• One failure you debugged (what broke, why, what changed)
• A short note (≤300 words) on how you’d increase IRL Quest Completion by 15%

We review for depth, not buzzwords.