Senior Backend Software Engineer, Case Intelligence

Expert Institute•New York, NY

16h

About The Position

Expert Institute is hiring a Senior Software Engineer for its Case Intelligence team, which builds Radar and MRR. These products turn court records, expert reports, depositions, and medical records into useful information for attorneys. The role focuses on backend and data engineering with an applied AI component, including production-scale document-processing pipelines, retrieval systems, and LLM workflows. The engineer will work directly with Product, the evaluation team, and engineering leadership, taking ambiguous problems from investigation through deployment and production support. A Senior Software Engineer owns complex projects from technical design through production operation, identifies failure modes, makes practical tradeoffs, improves quality over time, communicates risks early, contributes to technical direction, and helps other engineers make better decisions. Success includes reliable and recoverable document processing, measurable improvements in output quality, lower processing costs and latency as volume grows, and systems that are secure, observable, and supportable in production. Product and business partners should understand system capabilities, limitations, and planned improvements.

Requirements

At least five years of professional software engineering experience, including substantial work on backend systems or data pipelines.
Strong Python skills, including typing, Pydantic, and automated testing, plus solid SQL.
Production experience with AWS serverless or container services and event-driven systems.
Experience building with LLM APIs beyond prototypes, with attention to output quality, latency, and cost.
Experience processing PDFs, scans, OCR output, or other unstructured documents at scale.
Ability to investigate ambiguous problems, make sound technical decisions, and move work forward independently.
Clear written communication with technical and nontechnical partners.

Nice To Haves

Amazon Bedrock, RAG, vector search, reranking, or LLM evaluation tools such as Langfuse, pydantic-evals, or Label Studio.
Classic ML or NLP in production, including classifiers, embeddings, or entity resolution.
OpenSearch/Elasticsearch, Logstash, or Salesforce data integration.
Infrastructure as code, GitHub Actions, Datadog, and CloudWatch.
dbt, Athena, or Looker.
TypeScript, NestJS, GraphQL, or Angular.
HIPAA or other regulated data environments.
Legal technology or healthcare experience.
Productive use of AI coding agents such as Claude Code or Codex.

Responsibilities

Design, build, and operate event-driven pipelines using AWS services such as SQS, Lambda, ECS/Fargate, Step Functions, S3, and EventBridge.
Turn large volumes of unstructured documents into reliable, structured data.
Build production LLM workflows using Amazon Bedrock, OpenAI, and Gemini, including batch inference, structured outputs, model routing, and long-document processing.
Develop retrieval and machine-learning components using embeddings, OpenSearch, reranking, classifiers, and entity resolution where they improve results.
Work with the evaluation team to turn QA findings into measurable improvements in output quality.
Model and maintain data in PostgreSQL, DynamoDB, OpenSearch, and S3/Athena.
Make pipelines resilient to bad inputs and unreliable upstream systems through retries, dead-letter queues, idempotency, and backfills.
Own infrastructure, deployment, access controls, and observability for systems built.
Reduce processing time and cost without compromising quality.
Handle sensitive medical and legal information responsibly and keep technical documentation current.
Identify failure modes, make practical tradeoffs, improve quality over time, communicate risks early, contribute to technical direction, and help other engineers make better decisions.