Software Development Engineer III - Backend, Java

Arintra • Medical AI • Revenue Cycle & Medical Billing • Python • Java • 3 days ago

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Location

In office (Bengaluru)

Seniority

Middle · 6+ years exp

First seen by Alion on Oct 22, 2026.

Overview

Company

Impact

Profile match

Arintra

Arintra is a healthcare technology company based in Austin, Texas, and founded in 2019. The company provides an AI-driven autonomous medical coding and revenue assurance platform that integrates with electronic health record systems to automate insurance claim submissions. It operates across more than 23 medical specialties and multiple care settings, serving large health systems and provider groups throughout the United States.

arintra.com • HQ: Austin, United States • Medical AI • Revenue Cycle & Medical Billing • 51-200 employees • Est. 2019

Tech stack of Arintra

Backed by Y Combinator, Peak XV Partners, Spider Capital

Requirements:

6+ years in backend engineering, with at least 2 years in a lead or tech-lead capacity.
Strong proficiency in Java, Spring Boot, Hibernate/JPA, and microservices.
Demonstrated experience in HLD and LLD, and in designing, building, and deploying microservices-based systems in production.
Hands-on agentic SDLC experience within the last 12 months: you have shipped production software where AI agents were a primary part of the workflow. Concretely, experience with tools such as Claude Code, Cursor, Codex, Devin, Copilot Workspace/agent mode, Aider, or equivalent, applied to at least three of: design, implementation, code review, test generation, and production debugging/monitoring.
Practical judgment about where agents fail context management on large codebases, hallucinated APIs, silently wrong tests, review fatigue and concrete mitigations you've put in place.
Solid grounding in Git, CI/CD, and automated testing, including how these change when a large share of diffs are agent-authored.
Strong SDLC fundamentals and a track record of working with multiple teams.

Nice to have:

Built custom agents, subagents, or MCP servers against internal systems.
Prompt/context engineering at the repo scale (e. g., CLAUDE. md-style instruction files, retrieval over internal docs, codebase indexing).
Experience with LLM evaluation, regression harnesses, or accuracy pipelines.
Observability tooling (New Relic, Datadog, Prometheus/Grafana) and agent-assisted incident triage.
Healthcare, FHIR/HL7 or medical coding domain exposure.
Python for tooling and data work; PostgreSQL, Elasticsearch, or Neo4j; GCP or AWS.

Skills

"Agentic AI", "SDD", java, spring boot, "Agentic DLC", microservices

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