Full-Stack Enginee

VOYGR

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Location: Worldwide
Job Type: full-time
Salary: $4,000–$7,000/mo
Posted: April 30, 2026

Job Description

About the role

Why Voygr

VOYGR (YC W26) is building a real-world index every AI agent and App will need. Google says '4.2 stars, open till 10’ – VOYGR knows the chef left, wait times doubled, and locals moved on. This is 1T agentic queries per year that need every place verified and always fresh. Existing sources disagree with each other, go stale within months, and nobody maintains them fast enough.

Everyone loves maps. No one is building this at the infrastructure layer for AI. We do.

We are backed by Y Combinator and top investors with a multi-year runway. We already have real revenue and enterprise contracts. The founders are tech industry veterans (ex-Google Search & Maps, Meta, McKinsey, Harvard). You'll work directly with them.

The role

You'll work across our stack on a wide range of tasks – building APIs, data pipelines, ML integrations, product features, and infrastructure. The work changes week to week depending on what's most important. You'll get clear direction but also the space to figure out the best way to execute.

You

5+ years building and shipping production systems (or fewer if your background is unconventional and the work speaks for itself)
Comfortable across the full stack – backend, APIs, infra, frontend when needed
Experience with some combination of: search/IR, data processing at scale, ML systems, API design
AI-native – you use Claude Code, Cursor, or similar tools daily and know how to get the most out of them
Strong written and spoken English
AMER/EU/CIS time zones

Nice to have: Geospatial/POI data · eval systems · agentic frameworks · LLM prompting

Tech stack

Python, FastAPI · ML/AI: custom models, LLM APIs (OpenAI, Gemini, Anthropic) · PostgreSQL, PostGIS, DynamoDB · AWS (EKS, CloudWatch), Docker, Redis

What we offer

$4,000–$7,000/mo depending on location and experience
Remote – work from anywhere with at least 4 hours of overlap with US Eastern time
For the right person: path to relocating to the US, converting to full-time with equity and visa sponsorship

Interview Process

Send us a short message: what excites you about the role and why you're a good match
Intro call with founders (30 min)
Technical deep-dive
Paid trial project

🎯 Who is this job for?

This role suits a Middle to Senior Full-Stack Engineer with strong experience in Python, APIs, data pipelines, and cloud infrastructure (AWS, Kubernetes, PostgreSQL). The candidate should be comfortable working across the stack, integrating ML/AI systems, handling large-scale data, and using AI coding tools in daily development. They should also be adaptable to a fast-changing environment, owning features end-to-end and solving ambiguous, high-impact problems.

💬 Potential Interview Questions

How would you design a scalable API using Python and FastAPI?
Use asynchronous endpoints, proper request validation, and modular architecture. Combine with caching and rate limiting to handle high traffic.
What are the key considerations when building data pipelines at scale?
Ensure fault tolerance, idempotency, and efficient data processing. Use batch or streaming approaches depending on latency requirements.
How does PostgreSQL with PostGIS support geospatial applications?
PostGIS extends PostgreSQL with spatial data types and indexing. It enables efficient querying of location-based data.
How would you design a search system for real-time place intelligence?
Use indexing (e.g., inverted indexes), ranking algorithms, and caching. Combine multiple data sources and ensure freshness with frequent updates.
What are the benefits of using Kubernetes (EKS) in production systems?
Kubernetes provides orchestration, auto-scaling, and high availability. It simplifies deployment and management of containerized applications.
How do you integrate machine learning models into production systems?
Expose models via APIs, monitor performance, and handle versioning. Ensure scalability and low latency for inference.
What are best practices for designing distributed systems?
Focus on fault tolerance, eventual consistency, and observability. Use message queues and retries to handle failures.
How do you use Redis in high-performance systems?
Use Redis for caching, session storage, and rate limiting. It reduces database load and improves response times.
How can AI tools improve your development workflow?
They assist with code generation, debugging, and rapid prototyping. Proper usage increases productivity while maintaining quality.
How do you ensure data freshness and consistency in a real-time system?
Use event-driven updates, periodic revalidation, and conflict resolution strategies. Balance consistency with performance requirements.

📋 Job Summary

VOYGR is a Y Combinator-backed startup building a real-time “place intelligence” layer for AI apps, creating a constantly updated global index of physical locations for next-generation agents. As a Full-Stack Engineer, you’ll work across APIs, data pipelines, ML systems, and infrastructure using Python, FastAPI, AWS, PostgreSQL, and modern AI tools. This fully remote role offers $4K–$7K/month, flexibility across time zones, and the chance to collaborate directly with experienced founders from Google, Meta, and beyond. Join early to shape a high-impact product, work on cutting-edge AI infrastructure, and grow into a key role with potential equity and relocation opportunities.