Who We Are
Pattern Data is an AI-powered platform built for the complexities of mass tort litigation. We help leading law firms automate case analysis, accelerate settlement decisions, and manage high-volume inventories that were traditionally manual and time-intensive.
The problems we work on are complex and high-stakes, requiring precision, adaptability, and a deep understanding of both data and client needs.
We’re a collaborative, high-ownership team that moves quickly and takes pride in solving hard problems well. People at Pattern go deep to understand the “why,” build solutions that hold up, and stay focused on what drives real outcomes for our customers. We value transparency, thoughtful problem-solving, and authenticity in how we work together and we’re looking for someone who’s excited to contribute to a team that’s actively building and improving every day.
What You’ll Do
As a Software Engineer at Pattern Data, you will be involved throughout the product lifecycle - from idea generation, design, and prototyping to execution and shipping. The AI pod builds the systems that turn medical records and claim files into structured, reliable data. This role is focused on the engineering around our AI capabilities: the pipelines, evaluation, and review workflows that make the output something a law firm can act on. You will:
Build and operate LLM-backed pipelines for document extraction, classification, and validation
Measure and improve accuracy through evaluation datasets, regression suites, and metrics the business can act on
Build the review workflows where our team confirms and corrects AI output
Own the production details that determine reliability: prompt versioning, structured output validation, cost and latency management, retries, and fallbacks
Work with our litigation management team to identify where AI adds the most value
Our core stack of technologies:
Scala, TypeScript, PostgreSQL, GraphQL, Elasticsearch, AWS
What You’ll Bring
Bachelor's degree in Computer Science or a related technical discipline, or related practical experience
6+ years of experience in software engineering with strong fundamentals
Hands-on production experience with LLM APIs - prompting, structured outputs, retrieval, and tool use
A real point of view on evaluation: how you know the system is working, and how you know when it stops
Comfort with messy real-world data - OCR'd PDFs, scanned faxes, and forms filled out by hand
Curiosity and enthusiasm for tackling tough problems and delivering effective solutions
Great communication skills, and the ability to work seamlessly with technical and non-technical stakeholders
Ready to meet us?
Please apply directly through our website or Linkedin. We are excited to hear from you!
Pay Transparency Disclosure
The estimated base salary range for this role is $160,000-$220,000 per year, plus bonus and benefits.
At Pattern Data, our compensation philosophy is built around fairness, transparency, and market alignment. Base salary represents just one part of our total compensation package, which also includes performance-based incentives, comprehensive benefits, and other rewards.
Final compensation will be determined based on several factors, including skills, experience, qualifications, geographical location and internal equity across the team.
We understand that exceptional candidates bring unique backgrounds and strengths. If the scope of the role changes during the hiring process, we’ll update and communicate any adjusted range accordingly.
Pattern Data is committed to pay equity and to maintaining competitive, transparent compensation practices across all roles and teams.
Summary
Build and operate LLM-backed pipelines that turn medical records and claim files into structured, reliable data, including evaluation suites, review workflows, and production reliability for cost and latency. Requires 6+ years in software engineering plus hands-on production experience with LLM APIs, prompting, structured outputs, and retrieval.
Responsibilities
Build and operate LLM-backed pipelines for document extraction, classification, and validation; measure and improve accuracy through evaluation datasets, regression suites, and metrics; build review workflows to confirm and correct AI output; own production reliability: prompt versioning, structured output validation, cost and latency management, retries and fallbacks; work with litigation management team on AI value
Qualifications
Hands-on production experience with LLM APIs - prompting, structured outputs, retrieval, and tool use; point of view on evaluation; comfort with messy real-world data - OCR'd PDFs, scanned faxes, handwritten forms; curiosity for tough problems; great communication skills with technical and non-technical stakeholders
Education requirements
Bachelor's degree in Computer Science or a related technical discipline, or related practical experience
Experience requirements
6+ years of experience in software engineering with strong fundamentals
Benefits
plus bonus and benefits; comprehensive benefits; performance-based incentives