Full Stack Developer (.NET & Angular)

Senior Full Stack Developer — AI-Forward Development (.NET & Angular)

Saisystems Health is hiring an AI-forward Full Stack Developer with 5+ years of .NET and Angular experience and a US healthcare background to build and modernise ECM, our enterprise claims management platform

About the role

This is a hands-on full stack role where AI-assisted engineering is part of the job, not an optional extra. You will own tickets end to end — from design conversation through testing to production support — using AI coding assistants and agents to deliver faster while holding the quality and compliance bar of a regulated healthcare product.

The product. ECM manages the full claim lifecycle for US healthcare provider organisations: patient and encounter capture, coding and charge entry, eligibility, a configurable business-rules engine, clearinghouse claim transmission, ERA/835 payment posting, denial and AR work queues, patient statements, credentialing and executive reporting.

The engineering problem. ECM is a mature, high-volume, multi-tenant SaaS platform with tens of millions of claim and transaction rows, external BI consumers on the same database, and scheduled automation running alongside the API. The work mixes new feature delivery with deliberate modernisation — performance, observability, test coverage, security hardening and technical-debt reduction — in a system that cannot stop running.

Why AI-forward. We use AI across the engineering lifecycle and want engineers who already work this way: using agents and assistants to understand a large codebase, scaffold and refactor code, generate tests, review SQL and document changes — and who can explain every line they commit.

Key responsibilities

Front end (Angular)

• Build and enhance Angular screens — data grids, forms, multi-step claim and payment workflows, filters, dashboards and exports — that stay usable on large result sets.
• Work within a large existing codebase using NgRx state management, RxJS and component-driven design, refactoring incrementally rather than rewriting.
• Implement role-driven UI that respects access control and minimum-necessary display of sensitive data.

Back end (.NET) and database

• Implement ASP.NET Core Web API endpoints and service-layer logic (controller → interface → service) over stored procedures.
• Write and tune T-SQL procedures, views and queries against tables with tens of millions of rows; design indexes and read execution plans.
• Reason about locking and concurrency against simultaneous BI reads and scheduled background jobs.
• Build and maintain healthcare integrations: inbound and outbound X12 EDI (837, 835, 277CA, 999), clearinghouse SFTP exchange, ERA auto-posting and payer interfaces.

AI-forward development

• Use AI coding assistants and agents (Claude Code, GitHub Copilot, Cursor, Codex or similar) daily for codebase exploration, scaffolding, refactoring, unit-test generation, SQL and code review, debugging and documentation.
• Treat all AI output as a draft: review, test and understand it before committing; apply extra scrutiny to AI-assisted changes to stored procedures and production data paths.
• Identify and prototype practical AI use cases in the product and the development workflow — for example, test-case design, requirement clarification and release notes — within approved, compliant tooling.
• Share prompts, workflows and lessons learned so the whole team gets faster.

Quality, operations and compliance

• Diagnose production issues using Application Insights, logs and Query Store, and fix root causes.
• Write unit tests for new logic (xUnit, Moq, Jasmine/Karma) and partner with QA on regression coverage.
• Participate in code review as author and reviewer, and assess pre-merge impact across the develop → QA → UAT → staging → production pipeline.
• Follow HIPAA and secure-by-default practices: no PHI in logs, tickets, screenshots or AI tools; secrets in Key Vault; least-privilege access.
• Contribute to performance, quality and technical-debt work alongside feature delivery.

Collaboration

• Work from written requirements with US-based product and business stakeholders, ask clarifying questions and give realistic estimates.
• Write clear design notes, PR descriptions and status updates that support asynchronous, cross-time-zone work.

Required qualifications

Experience

• 5+ years of professional full stack development with .NET and Angular in production systems.
• 2+ years working on US healthcare software — revenue cycle management, medical billing, claims, practice management, EHR or payer systems.

.NET and database

• Strong C# and ASP.NET Core Web API (.NET 6 or later); comfortable with Entity Framework Core and/or Dapper.
• Working SQL Server / T-SQL: can write a non-trivial stored procedure, read a query plan and explain why a query is slow.

Angular

• Strong Angular (12+) with TypeScript, RxJS and component-driven design; able to work in a large existing codebase without rewriting it.

AI-forward engineering

• Demonstrated daily use of at least one AI development platform — Claude / Claude Code, GitHub Copilot, ChatGPT / Codex, Cursor or similar — for code generation, refactoring, test writing, debugging and documentation.
• Effective prompting and context management on a large, unfamiliar codebase, not just generic snippets.
• Verification discipline: can explain every line committed, and can show examples of catching and correcting flawed AI output.

Healthcare domain

• Working knowledge of the claim lifecycle: charge entry, claim submission, adjudication, remittance, denials and AR follow-up.
• Familiarity with HIPAA X12 transactions (837, 835, 277CA, 999) and CMS-1500 / UB-04 claim formats.
• Understanding of HIPAA Privacy and Security Rule obligations and how they shape logging, access control and data handling.

Engineering practice

• Git, pull-request workflow and CI/CD (Azure DevOps or similar).
• Ability to work from written requirements, ask good clarifying questions and give realistic estimates.
• Willing to work from the Pune office full time.

Preferred qualifications

• Experience with agentic AI workflows (for example, Claude Code or Copilot agents) for multi-file changes, test generation or code migration.
• Experience integrating LLM APIs (Azure OpenAI, Anthropic, OpenAI) into .NET applications — prompt design, retrieval-augmented generation (RAG), structured output and evaluation — within HIPAA-compliant boundaries.
• Exposure to AI use cases in RCM such as denial prediction, coding assistance, document extraction or claim scrubbing.
• Microsoft Azure services: App Service, WebJobs, Blob Storage, Key Vault, Service Bus, Redis, Application Insights, Entra ID.
• NgRx or another Redux-style state library; SignalR or other real-time patterns.
• EDI tooling such as EdiFabric; SFTP and clearinghouse integrations.
• xUnit / NUnit / Jasmine-Karma testing experience.
• Reporting or BI exposure (Power BI, SSRS).
• Certifications (any of): Microsoft Azure Developer Associate (AZ-204), Azure AI Engineer Associate (AI-102), or a healthcare credential such as AAPC or HFMA coursework.

Education: Bachelor's degree in Computer Science, Engineering or a related field — or equivalent demonstrable professional experience. What you have built and shipped counts more than the credential.

Core competencies and success measures

Ways of working

• Evidence over assertion — claims about performance or impact are backed by a measurement or a source reference.
• Production respect — the system handles live claims and money; changes are weighed for their effect on real data before merge.
• Clear written communication — design notes, PR descriptions and status that someone outside your head can follow.
• Cross-time-zone collaboration — close work with US-based product and business stakeholders; asynchronous clarity matters as much as meetings.
• Continuous learning — keeping current with AI tooling as it changes how this work is done.

Compliance, security and responsible AI use

• ECM processes Protected Health Information (PHI). All engineers complete HIPAA training and are bound by Saisystems Health security and confidentiality policies.
• No PHI, patient data, credentials, production connection strings or confidential business data is ever entered into an external or unapproved AI tool.
• AI is an accelerator, not a substitute for engineering judgement; accountability for correctness stays with the engineer.
• AI-generated code is reviewed to the same standard as hand-written code, with added scrutiny for stored procedures and production data paths.
• Secure-by-default habits: no PHI in logs, tickets, screenshots or non-production data; least-privilege access; secrets in Key Vault, never in source.
• Design decisions account for audit, access control and data-retention requirements of a regulated product.
• Employment is subject to a background check and a signed confidentiality agreement.

Equal opportunity: Saisystems Health is an equal opportunity employer. HR to confirm the standard EEO statement and any compensation or benefits wording before posting