Nuuly Senior Software Engineer Nuuly Anywhere in the World

Neura Market; Philadelphia (Philadelphia County); On-site; USD 140,000 - 180,000; Full time

Job summary

Nuuly is seeking a Senior Software Engineer to join our Technology team in Philadelphia. You will help mature our cloud-based microservices platform that powers our online customer experience and garment distribution center logistics.

You will design, implement, test, and deploy features in a scalable JVM-based environment, using Kotlin/Spring and modern data stores. You will mentor others, participate in incident response, and drive reliable, low-downtime deployments.

Qualifications

• Experience with JVM languages (Java/Kotlin/Scala) and microservices architecture.
• Strong understanding of RESTful APIs, HTTP protocols, and service integration patterns.
• Experience with testing, TDD, and building reliable systems.

Responsibilities

• Produce architectural proposals and contribute to platform evolution decisions.
• Collaborate with product teams on technical feasibility and stakeholder features.
• Mentor junior engineers through code reviews and design discussions.

Skills

Java/Kotlin

Microservices

Distributed systems

Testing/TDD

AI tools

Cloud platforms

Tools

Docker

Kubernetes

Postgres

AlloyDB

Job description

Headquarters: Philadelphia, PA
URL: https://www.nuuly.com/

Nuuly is hiring a Senior Software Engineer to join our Technology team. Building performant scalable cloud service environments is hard. Nuuly knows this firsthand, having built a cloud-based microservices platform from the ground up to power our online customer experience and drive the logistics and processing of our garment distribution centers. We're looking for a Senior Engineer with the initiative and expertise to help mature this platform into a stable, scalable, and robust backbone for launching the next wave of Nuuly innovations.

You'll need strong experience designing and building microservices backed by relational and non-relational databases. Solid confidence with JVM-based tools such as Kotlin, Spring, and data persistence with Postgres and other database technologies. You’ll also need a reasonable amount of aptitude in designing and integrating Kubernetes services with cloud-based platform APIs such as Google Cloud Platform (GCP), AWS, or Azure focused on driving toward zero-downtime deployments.

As a Senior Engineer, you'll bring experience that extends beyond personal code contribution: leading design for moderately complex features, driving communication between teams, providing critical feedback, coordinating with others, and providing mentorship as needed. You'll participate in incident response and post-mortem processes to improve system reliability. You should be adept at picking up new technologies and patterns and comfortable discussing and debating the pros and cons of various approaches. Most of all, you should be ready and willing to tackle new challenges with a supportive team of creative and hard-working professionals.

Responsibilities:

• Producing architectural proposals and engaging in discussions and decision-making for new features and platform evolution
• Collaborating with the product team to design solutions for stakeholder features and inform product decisions through technical feasibility analysis
• Mentoring junior engineers through code review, pair programming, and design discussions
• Delivering the whole lifecycle of deployable features: design, code, testing, configuration, documentation, deployment, and support
• Contributing to operational guidelines, system reliability practices, and post-mortem analysis for production incidents
• Teaching and enforcing development methodologies while proactively identifying improvement opportunities in codebase, tooling, and processes
• Collaborating with QA and Platform Engineering teams to test code and keep our integrated testing environments unblocked
• Providing technical guidance to cross-functional teams on integration approaches and system constraints to deliver features and evolve our architecture

Qualifications:

• 5-7 years of software engineering experience with ~2 years of senior-level responsibilities such as taking ownership of designs or projects and working to coordinate work across teams
• Operational knowledge of one or more server-side object-oriented programming languages (Java, Kotlin, Scala, or other JVM languages preferred; Python, Go, Node/TypeScript also considered)
• Able to talk comfortably about microservices architecture, distributed system design, streaming data, messaging technologies, and database design patterns
• Experience and enthusiasm for testing, test-driven development, and building reliable systems
• Proficient with leveraging AI tools in day-to-day development tasks such as code generation, debugging, and documentation
• Able to hit the ground running and quickly familiarize yourself with an existing codebase and toolset
• Able to propose and walk through solutions in technical leadership discussions and communicate effectively across functional teams
• Operational knowledge of Java, Kotlin, Scala, or other JVM languages (Python, Go, Node/TypeScript also considered)
• Strong experience designing, building, and operating microservices architectures; expertise with RESTful APIs, HTTP protocols, and service integration patterns
• Experience with Google Cloud Platform (GCP) or other major cloud providers (AWS, Azure); knowledge of container technologies (Docker, Kubernetes)
• Hands-on experience with relational databases (Postgres, AlloyDB) and understanding of data modeling, query optimization, and schema evolution.
• Understanding of distributed system design patterns, consistency models, and trade-offs in microservices architectures (e.g., Kafka, Spark, Storm , etc.)

AI/LLM Proficiency:

• Practical experience using Large Language Models (ChatGPT, Claude, Cursor, Windsurf, Copilot etc.) for work tasks
• Understanding of prompt engineering and how to provide effective context to AI tools
• Familiarity with structured AI guidance methods (system prompts, rules files, agent configurations)
• Knowledge of AI tool integration concepts (MCP, connectors, agentic workflows)
• Ability to identify opportunities where AI can drive efficiency improvements