Software Development Engineer III - Backend, Java
Arintra · Bengaluru · onsite · Posted 84d ago
About a minute. You'll make an account on the way through.
About this role
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.
Sourced from instahyre
Skills
About Arintra
Arintra
11-50
employees
2020
6 years old
Austin
US
About
US hospitals and clinics are losing $125B every year due to delayed and inaccurate medical coding. Arintra is solving this problem by automating medical coding using AI and clinical NLP. Arintra converts a patient chart instantly into insurance claims with 96% accurate medical codes and zero human intervention.
Arintra solution is specifically tailored to cater to the varying requirements of ambulatory and outpatient specialties, emergency department services, and inpatient settings, ensuring comprehensive coverage across all healthcare domains.
Arintra’s software leverages proprietary artificial intelligence and natural language processing algorithms to process patient charts directly from the EHR to create a direct-to-billing claim. Arintra autonomously goes through every stage of the claim submission process and ensures a clean claim for optimal reimbursements without any human intervention. Arintra is integrated with all the top EHRs to ensure effortless implementation without any change in the workflow.
Arintra’s medical coding software offers two powerful modes for medical coding: autonomous coding mode and assisted coding mode. In autonomous coding mode, direct-to-billing claims are generated autonomously with high accuracy, streamlining the billing process for healthcare provider organizations. Whereas, assisted coding mode allows medical coders to meticulously review and optimize charges before submission, leading to increased efficiency and precision in the coding process. With Arintra, healthcare provider organizations can rely on precise direct-to-billing claims that include essential codes like E/M levels, CPT, ICD-10, HCC, HCPCS with appropriate modifiers and units.
Arintra’s coding solution provides extensive coverage and flexibility, catering to various coding domains such as professional coding, professional-fee coding, facility coding, and inpatient coding.
Industries
Employee ratings
7 reviews
Culture
2.0
Career growth
2.0
Work-life
1.6
Find them on