- Core Functions of the Role
- Design, build, test, deploy, and maintain production applications and services.
Develop well-designed APIs and backend services using Kotlin/Java, Python, Spring Boot, and related technologies.
Work with relational and NoSQL databases, search technologies, and large datasets.
Contribute to distributed systems and microservice architectures running in AWS.
Participate throughout the development lifecycle: planning, design, estimation, implementation, testing, deployment, and continuous improvement.
Use AI coding assistants and agents to accelerate research, planning, development, testing, debugging, refactoring, and documentation.
Critically review AI-generated implementations and remain accountable for quality, correctness, security, and maintainability.
Collaborate with engineers, product managers, and stakeholders to turn requirements into high-quality technical solutions.
- Contribute to design discussions, code reviews, engineering standards, and development practices.
- About You
- 2+ years of professional software development experience for mid-level candidates or 6+ years for senior-level candidates.
Strong computer science and software engineering fundamentals through a CS-related degree or equivalent professional experience.
Experience designing and building production web applications, APIs, or backend services.
Strong understanding of HTTP, REST, API design, relational databases, SQL, data modeling, and database design.
Strong proficiency in Kotlin/Java with Spring Boot or a comparable JVM framework, OR Python and its modern application ecosystem.
Willingness and ability to work across JVM and Python technologies as needed.
Experience writing maintainable, well-tested production software.
Strong debugging, problem-solving, and analytical skills.
Experience with Git and modern collaborative development workflows. AI-Augmented Software Development AI-assisted development is an important part of how we approach modern software engineering. We are particularly interested in candidates who meaningfully use tools such as Claude Code, OpenAI Codex, GitHub Copilot, or comparable coding agents in their regular workflow.
We want engineers who use AI to expand what they can accomplish while retaining responsibility for understanding and validating the result.
Use AI to understand unfamiliar codebases, research technologies, plan implementations, write and modify code, develop tests, debug problems, refactor systems, and automate repetitive work.
Critically evaluate AI-generated solutions, recognize incorrect assumptions, validate implementations, and know when direct engineering investigation is the better approach.
- Experience with repository-level agent instructions, reusable agent workflows, MCP integrations, custom tooling, or agentic development processes is a plus.
- Additional Experience We'd Value
- Experience with some of the following is preferred; we don't expect every candidate to have all of them:
AWS
Terraform or other infrastructure-as-code technologies
Docker or other container technologies
CI/CD pipelines
Elasticsearch or other search technologies
Microservices and distributed systems
Event-driven architectures
Linux, command-line tooling, and Bash
- Large-scale or data-intensive applications
- For Senior-Level Candidates
- Strong system-design and architectural judgment.
Ownership of systems from design through production.
Ability to evaluate scalability, reliability, performance, maintainability, security, and cost tradeoffs.
Ability to diagnose complex problems across distributed systems.
Ability to turn ambiguous requirements into clear technical approaches.
Thoughtful code and design review skills.
Ability to mentor engineers and improve team effectiveness.
