Spontaneous Events Meet AI for Friendship Building in the Digital Era
Founding Backend Engineer – Marketplace and Logistics
Location
New York
Posted
7 days ago
Salary
0
Seniority
Senior
Job Description
Founding Backend Engineer – Marketplace and Logistics
Flocker
• Design, build, and maintain Flocker’s backend services and APIs (FastAPI + PostgreSQL, migrating to DynamoDB over time). • Implement authentication, session management, and secure cookie flows (FastAPI Users + CloudFront). • Develop and scale real-time data pipelines (Kinesis, Lambda, S3) for interaction logging and personalization. • Build and optimize media handling pipelines (image/video upload, compression, CDN delivery via CloudFront). • Architect and tune database schemas (Postgres → DynamoDB single-table design) with focus on cost-efficient scale. • Collaborate with mobile/frontend engineers to deliver seamless, low-latency user experiences. • Engage in the full software development lifecycle: design, coding, testing, deployment. • Work in a fast-moving, agile startup environment — iterating quickly and adjusting priorities based on learning and feedback.
Job Requirements
- 5+ years designing, building, and scaling backend systems to millions of users.
- Expert in modern backend development (FastAPI, Django, Flask, or similar).
- Proven ability to build and launch products (startup, side project, or even a failed venture).
- Experience with relational databases (Postgres/MySQL) and exposure to NoSQL systems.
- Track record of shipped products or platforms we can see live today.
- Leadership ability, self-motivation, and comfort navigating ambiguity.
- Ready to operate with founder-level ownership and commitment.
- Bonus: Experience with real-time data pipelines, cloud infrastructure (AWS), or consumer apps.
- Bonus: Demonstrated experience building or scaling marketplace platforms with integrated logistics flows (matching, routing, ticketing, or fulfillment systems). e.g. Uber, Lyft, Airbnb, or Doordash.
Benefits
- Compensation: Salary plus equity
- Opportunity to be part of a dynamic startup environment
Related Guides
Related Job Pages
More Backend Engineer Jobs
Backend Developer, AI Trainer
Anyone AIWe invest in people from Latam to bridge the talent gap in AI.
• Design and implement multi-file coding tasks across bug fixing, feature development, refactoring, and testing • Write clear natural-language specifications and reference implementations • Develop and extend unit and integration test suites • Review peer-generated tasks for correctness, clarity, and realism • Identify edge cases, ambiguities, and potential failure modes • Ensure alignment between specifications, code, and expected outputs
Backend Developer – AI Trainer
Anyone AIWe invest in people from Latam to bridge the talent gap in AI.
• Design and implement multi-file coding tasks across bug fixing, feature development, refactoring, and testing • Write clear natural-language specifications and reference implementations • Develop and extend unit and integration test suites • Review peer-generated tasks for correctness, clarity, and realism • Identify edge cases, ambiguities, and potential failure modes • Ensure alignment between specifications, code, and expected outputs
Back-End Developer III
GFT TechnologiesAs a pioneer for digital transformation GFT develops sustainable solutions across new technologies.
• Develop and optimize applications based on Large Language Models (LLMs), ensuring response quality and prompt efficiency; • Agent Orchestration: Design and implement complex flows and multi-agent systems using LangChain and LangGraph for reasoning automation; • Data Architecture for AI: Implement RAG (Retrieval-Augmented Generation) strategies, including vector databases and indexing techniques for semantic search; • Backend Development: Build robust, high-performance APIs in Python (FastAPI/Django) to serve AI models at scale; • Cloud Scalability: Develop and deploy solutions using the AWS ecosystem, focusing on AI services, serverless computing, and containers; • Quality and Monitoring: Establish model testing standards (evaluation of hallucinations, latency, and cost) and ensure the development lifecycle (LLMOps).
• Own the Python engine layer for algorithms and data processing • Process large volumes of operational schedule data through constraint evaluation • Generate periodic staff rosters by solving constraint problems • Real-time task assignment using proximity scoring against live employee location data • Scheduled KPI aggregation and SLA scoring across all modules
