Senior .NET Developer - AI & Intelligent Automation (Health Insurance Platform)
Role details
Job location
Tech stack
Job description
You will work within a Scrum team (3-week sprints), contributing to our existing .NET/Angular platform while leading the design and implementation of AI-centric features and integrations. You will partner closely with our ML engineering and infrastructure teams to leverage our in-house GPU infrastructure and Run.ai platform for model training, fine-tuning, and inference at scale., Core Product Development (.NET / Angular / Messaging)
- Design, build, and maintain core product features using:
- .NET (C#), ASP.NET Core
- Angular
- SQL Server and MongoDB
- RESTful APIs and NServiceBus
- Contribute to application architecture decisions, refactoring initiatives, and shared platform components.
- Ensure new AI features are robust, secure, explainable, and integrated cleanly into the existing product.
AI Capability & Feature Development
- Work with Product Management and domain experts to identify high-value AI use cases, initially focusing on automating processing of claims invoice documents (e.g. OCR, document classification, data extraction, validation workflows).
- Design, implement, and integrate AI services and pipelines, such as Machine learning / rules-based components for classification, anomaly detection, and routing (e.g. flagging potentially incorrect invoices or exceptional cases).
- Fine-tuned language models or specialized inference models deployed on our in-house GPU infrastructure.
User Experience & Workflow Automation
- Work closely with Product and UX to design AI features that give clear benefits to end-users (time saved, errors reduced, fewer clicks).
- Implement workflow automation and orchestration
Requirements
Do you have experience in REST?, * Strong commercial experience building enterprise applications with: *
- .NET / C#
- ASP.NET Core
- Angular
- SQL Server and MongoDB
- RESTful APIs; NServiceBus or equivalent service bus/messaging platform.
- Demonstrable experience in at least one of:
- Implementing AI/ML-driven features in a production product, or
- Building document processing / intelligent automation workflows (OCR, classification, extraction, validation).
- Familiarity with common AI/automation building blocks such as:
- OCR and document understanding (e.g. cloud services or libraries).
- Entity extraction, text classification, or similar NLP tasks.
- Rule engines, workflow engines, or BPM/orchestration tools.
- Strong understanding of non-functional requirements for AI features:
- Performance and throughput for high-volume processing.
- Data protection, privacy, and access control.
- Auditability, traceability, and explainability for automated decisions.
- Solid grounding in software engineering fundamentals: design patterns, testing strategies (unit/integration), CI/CD concepts, secure development lifecycle., * Product-minded engineer who thinks in terms of user outcomes, not just technology.
- Pragmatic with AI: focused on solving real user problems and automating meaningful work, rather than technology for its own sake.
- Comfortable working in ambiguous problem spaces and iterating quickly based on feedback.