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Gather AI is building a vision-powered platform that uses autonomous drones and existing equipment to digitize warehouse operations, capturing real-time data to improve efficiency and reliability in supply chain management.
You'll join a small, distributed engineering team building and operating the production systems behind Gather AI's warehouse intelligence platform. This includes APIs, integrations, data pipelines, databases, and application services used by customers and internal teams daily.
As an SDE II, Full Stack, you'll build and run the web platforms behind Gather AI's products—Drone Vision, MHE Vision, and SAGE—from customer-facing dashboards down to APIs, integration layers, and data pipelines. This is a fully remote, hands-on role for someone early in their career with production software experience who wants broader ownership.
You'll work alongside senior engineers, taking on well-scoped features, integrations, and platform improvements while developing deeper expertise across APIs, backend services, databases, distributed systems, infrastructure, and production reliability. You won't be limited to coding against someone else's design; you'll contribute to technical decisions, troubleshoot production systems, work through failures and performance issues, and gradually take ownership of components from development through deployment and ongoing support.
Key responsibilities include:
- Build and maintain production backend services using Python and Node.js/NestJS
- Design, build, and maintain REST APIs and integrations with internal and external systems
- Work with PostgreSQL in production, including schema design, complex queries, indexing, and performance tuning
- Build and support asynchronous workflows using message queues and distributed system patterns
- Apply caching strategies across application and data layers
- Take features through the full software development lifecycle, including development, testing, deployment, monitoring, troubleshooting, and iteration
- Containerize and deploy services using Docker, Kubernetes, and CI/CD pipelines
- Monitor production systems using logs, dashboards, metrics, and observability tools
- Diagnose and resolve production issues across APIs, integrations, queues, databases, and multi-service workflows
- Contribute to secure development practices including authentication, authorization, and secrets handling
- Work closely with senior engineers on technical design and architecture decisions
- Identify opportunities to improve code, reliability, performance, and engineering processes
- Collaborate with Engineering, Security, Customer Success, Product, and other teams
Because the team is distributed across multiple time zones, clear written communication, initiative, and the ability to make progress independently are especially important.
**Requirements:**
- 2–5 years of professional software engineering experience building and operating production software
- Engineering degree in Computer Science or equivalent practical experience
- Production experience with Python and Node.js/NestJS, with strong production depth in at least one and working experience with the other
- Experience building production-grade APIs, microservices, or backend systems and seeing them through deployment and ongoing operation
- Strong SQL fundamentals and hands-on relational database experience, including complex queries, indexing, schema design, and production performance troubleshooting
- Experience designing and maintaining REST APIs, not only consuming them
- Experience integrating with external systems and understanding real-world concerns such as retries, duplicate processing, failure handling, and unreliable dependencies
- Working knowledge of distributed systems concepts including asynchronous processing, message queues, retries, consistency, and failure recovery
- Understanding of caching, including what to cache, where caching should occur, and how invalidation is handled
- Experience with message queues or asynchronous processing technologies such as Kafka, RabbitMQ, SQS, or equivalent
- Experience with Redis or another caching technology
- Experience with Azure or another major cloud provider, deploying and debugging, using Docker, Kubernetes, and CI/CD pipelines
- Familiarity with Git and modern code review workflows
- Understanding of secure coding fundamentals including authentication and authorization, secrets handling, injection risks, and data exposure
- Experience working with production systems beyond simply writing code, including monitoring metrics, investigating performance, responding to failures, and improving systems after issues occur
- Strong written and verbal communication skills in English, with the ability to document decisions, explain tradeoffs, write clear PRs and design notes, and raise blockers early
- A collaborative and curious approach, with the willingness to contribute ideas, ask questions, accept feedback, and work across component boundaries when needed
**Nice to Have:**
- Experience building or operating data pipelines, including handling failures, backfills, and data-quality issues
- Familiarity with data engineering concepts such as warehouse or lakehouse modeling, dbt or equivalent, and ETL/ELT design
- Experience with orchestration or streaming technologies such as Airflow, Flink, or similar
- Familiarity with BI and visualization tools such as Metabase, Apache Superset, or equivalent
- Experience with multi-region or geo-distributed systems
- Experience in logistics, warehouse management systems, robotics, or another physical-world technology environment
- Experience incorporating AI-assisted development into the software development lifecycle
- Exposure to GenAI code-validation practices or engineering guardrails
