Agentic Systems Engineer Intern (Summer 2026)

Our MissionAt 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 AreHeadquartered 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 MoatPhygtl 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 ForYou 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 EvaluateWe prioritize: Systems clarity (state + failure thinking) Execution speed Ownership Depth over pedigree Why Join PhygtlWork 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 MatterYour 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 ScaleYou’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 EnvironmentWe value: Meritocracy over pedigree Shipped systems over slide decks Clear thinking over buzzwords Ownership comes early. Responsibility scales with performance.Build a Rare Skill SetYou’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 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.Originally posted on Himalayas