Software Development Engineer (Mid-Level / SDE)- Hybrid

Zipliens is a leading lien resolution company that specializes in streamlining the lien process for personal injury law firms. Our work helps law firms operate more efficiently and helps the injured people they serve access settlement funds more quickly and accurately. We are looking for engineers who want to build the systems that make complex, data-heavy products work at scale.

We are looking for a Software Development Engineer to join our team, building the next generation of applications for the legal industry. After several years of high growth, Zipliens has become a leader in lien resolution, a process required in most personal injury settlements. The software we build supports that work, giving it clear, real-world impact beyond the technical challenges.

We're scaling engineering significantly this year. You'd be joining a codebase with established patterns and helping extend those patterns as the team grows several times over. You'll have context available rather than a blank slate, and senior engineers on hand when a decision warrants one.

Over the coming year, we're building large-scale data processing, smarter automation of staff workflows, ML/LLM systems that extract structure from medical records and lien correspondence, and customer-facing experiences that make the lien process more transparent. In this role, you'll work across our React and Python/Django stack: building features, resolving issues, and contributing to system improvements alongside product, operations, and your fellow engineers.

We're hiring for this role at two levels. The difference is scope and independence — how large a piece of work you carry, and how much of it you shepherd through review and deployment on your own — not the kind of work you'd do.

We also build with AI as a first-class part of the workflow: agentic coding tools, plus internal skills and harnesses we've written ourselves. Not autocomplete. You'd be expected to use them well and to improve them.

• 2+ years of software development experience building and maintaining systems in production.
• Working experience with Python/Django (preferred) or a comparable framework (Node.js, Rails, Laravel).
• Working proficiency in React.
• Working SQL and PostgreSQL, including writing and reasoning about queries against large tables.
• Hands-on AWS experience — EKS/EC2, RDS, S3, and queueing (SQS or similar). You should understand the infrastructure your services run on, not treat it as someone else's problem.
• Proficiency in at least one technical area and a functional understanding of the applications your team owns.
• Strong problem-solving skills and a willingness to take on unfamiliar work.
• Clear written and verbal communication; you'll be explaining technical constraints to non-technical stakeholders.

• →Build and maintain features across our Python/Django backend and React frontend, writing code that is clean, readable, and consistent with our team's conventions.
• →Develop and ship features, shepherding your own work from first commit through review, QA, and deployment. How much support you get there depends on where you land; the expectation of ownership doesn't change.
• →Operate what you build: troubleshoot production issues, debug your services in AWS, and follow security practices appropriate to sensitive legal and medical data.
• →Build and maintain backend services and data processing workflows over large datasets, automating what's currently manual.
• →Work with product and operations to turn acceptance criteria into features our staff and clients actually use — asking questions where they're unclear, and pushing back where they're wrong.
• →Work with internal stakeholders to translate business needs into technical solutions.
• →Contribute to architecture and scalability improvements under the guidance of senior engineers.
• →Participate in code reviews, both giving thoughtful feedback and acting on it.

• Experience using or experimenting with agentic coding tools, and interest in building tooling around them.
• Hands-on experience with LLM or ML features, whether in production or through prototypes and experimentation: prompting, evaluation, and understanding how they fail.
• Experience with document processing or extraction from unstructured data.
• Experience integrating third-party or partner APIs, especially where the data is inconsistent, and the counterparty's documentation isn't solid.
• Experience handling sensitive data such as PHI, or working under HIPAA-style requirements.
• Familiarity with Kubernetes. We have an SRE who owns the cluster; you won't be running it, but you'll be deploying to it and debugging your services in it.