SDE III

Company: Arintra

Website: Visit Website

LinkedIn: Visit LinkedIn

Business Type: Agency/Studio

Company Type: Product

Business Model: B2B

Funding Stage: Series B

Industry: Software Development

Job Description

About Arintra

Arintra is an artificial intelligence-based healthcare and clinical solutions provider, backed by YCombinator.

We have built a clinically-driven AI-powered technology to autonomously generate accurate medical codes to improve billing for hospital systems in the USA. Through our product, we aim to reduce administrative hassles and maximize revenue for healthcare providers by automating their coding and billing with zero workflow change.

Responsibilities

• Design, build and own production-grade LLM agents used in real healthcare workflows.
• Build the backend services, APIs and tools that agents interact with.
• Design agent workflows including tool calling, orchestration, context, memory, guardrails and failure handling.
• Build rigorous evaluation systems using golden datasets, deterministic checks, LLM-as-judge, human review and trajectory evaluation.
• Define and track measurable quality metrics such as precision/recall/F1, task success, tool-call accuracy and regression rates.
• Build eval-gated release processes including automated regression suites, shadow/canary deployments and rollback mechanisms.
• Instrument and monitor agents in production across quality, reliability, latency and cost.
• Debug failures across prompts, models, tools and underlying backend services.
• Make pragmatic decisions around model selection based on accuracy, cost and latency.
• Know when an agent is the right solution and when deterministic software is better.
  
  

Requirements

• 6+ years of software engineering experience, with strong ownership of production backend systems.
• 1+ year of experience building LLM agents in production with real users.
• Experience owning at least one agent end-to-end design, prompts, tools, evals, deployment and post-launch improvement.
• Strong backend engineering and distributed systems fundamentals.
• Hands-on experience evaluating AI systems against real datasets and clearly defined metrics.
• Strong understanding of APIs, production architecture, reliability and observability.
• Ability to reason about model choice, prompting, tool design, context and failure modes.
• Strong ownership and ability to work across engineering, product and domain teams.
  
  

Innovation and commitment to our mission are core to our DNA and through our shared values, we foster an environment of inclusion, empowerment, accountability, and fun!