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Salary
≈ $32k – $88k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Staff · 9+ years exp

First seen by Alion on Oct 7, 2026.

Overview
Company
Impact
Profile match
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.

Responsibilities:

  • Build and lead a high-performing engineering team developing production Agentic AI systems.
  • Own both delivery and technical outcomes: quality, reliability, latency, and cost.
  • Partner closely with product, AI/data science, and healthcare domain experts to turn complex workflows into reliable products.
  • Drive architecture and design reviews across agents, backend services, tools, and integrations.
  • Establish evaluation as a core engineering discipline using golden datasets, measurable metrics, regression testing, and release gates.
  • Challenge technical decisions around prompts, models, tool design, orchestration, guardrails, and agent architecture.
  • Ensure production AI systems have strong observability, failure handling, and incident-management practices.
  • Hire exceptional engineers and create clear standards for engineering excellence.
  • Coach and mentor engineers while maintaining a high bar for ownership and execution.
  • Own production failures with the team and ensure learnings translate into better architecture, tooling, and processes.

Requirements:

  • 9+ years of engineering experience, including 2+ years directly managing engineers.
  • Strong backend engineering foundation with experience owning production services before moving into management.
  • Experience leading a team that has shipped LLM agents to real users in production for 1+ year.
  • Strong system design and architecture fundamentals.
  • Hands-on understanding of agent evaluation, including golden datasets, metrics, and release gates.
  • Ability to challenge technical decisions around model choice, agent architecture, reliability, and cost.
  • Experience hiring, mentoring, and developing strong engineers.
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