Note: The job is a remote job and is open to candidates in USA. Optivate is a leading provider of healthcare technology software solutions for ophthalmologists and eye care specialists. They are seeking a full-stack .NET engineer who is AI-native to design and ship AI-driven features and integrate AI capabilities into their ophthalmology platform.
Responsibilities
- Design and ship AI-driven features across our ophthalmology platform
- Work with third-party LLM integrations
- Develop custom ML models
- Build domain-specific enhancements using clinical data
- Design, build, and maintain full-stack features across our ophthalmology platform — backend services and APIs in .NET/C# (.NET Core, .NET 10) and responsive frontend interfaces in HTML/CSS
- Use AI-native and agentic development workflows (e.g., Cursor multi-agent pipelines for decomposition, architecture, implementation, QA, and review) to move quickly while keeping code clean and reliable
- Design and integrate AI-powered features — including third-party LLM integrations — that fit safely into clinical software
- Troubleshoot and improve distributed systems
- Establish and participate in code review processes
- Work within an agile framework, contributing to: Sprint planning, Daily standups, Retrospectives
- Write clean, maintainable, testable code, and establish and participate in code review
- Collaborate across product, clinical, and engineering teams
- Contribute to architectural decisions, including where and how AI fits into our systems
- Work within an agile framework: sprint planning, daily standups, and retrospectives
- Integrate third-party LLMs (OpenAI, Anthropic, Azure OpenAI, Hugging Face) into production features
- Build retrieval pipelines using embeddings and vector databases (Pinecone, FAISS, Weaviate) and implement semantic search
- Develop prompt engineering strategies with testing and versioning
- Design evaluation approaches that measure accuracy, reliability, hallucination rates, and clinical relevance
- Collaborate on deploying, monitoring, and maintaining AI services in production
- Optimize AI feature performance, latency, and cost
Skills
- 3–7 years of professional software development experience with strong full-stack delivery
- Strong, current experience with .NET/C# (.NET Core and/or .NET 10)
- Proficiency building responsive UIs with HTML/CSS
- Demonstrated fluency with AI-assisted and agentic development tooling (e.g., Cursor, Claude Code, Copilot), ideally including multi-agent development workflows
- Experience integrating LLM APIs into real, shipped systems (does not need to be the bulk of your career — but you've done it and understand the tradeoffs)
- Solid foundation in data structures, algorithms, API design, and distributed system design
- Experience with at least one major cloud platform (AWS, Azure, or GCP)
- Familiarity with model limitations, evaluation tradeoffs, and the realities of running AI in production
- Experience working in collaborative environments with exposure to Git version control and branching strategies
- Experience working in collaborative environments with exposure to Agile methodologies (Scrum/Kanban)
- Experience working in collaborative environments with exposure to task/story management tools
- Experience working in collaborative environments with exposure to code reviews
- Experience working in collaborative environments with exposure to architectural discussions
- Experience working in collaborative environments with exposure to cross-functional collaboration
- AI-native mindset (data, models, feedback loops, iteration)
- Pragmatic builder who understands production constraints
- Comfortable with ambiguity in emerging AI spaces
- Strong communicator, especially explaining AI tradeoffs
- Motivated to apply AI in healthcare where safety and reliability matter
- Experience with Blazor, particularly Blazor Hybrid and .NET MAUI for building cross-platform applications on a shared .NET codebase
- Experience building or fine-tuning ML models (NLP, structured data, computer vision)
- Enhancing foundation models with RAG, fine-tuning, embeddings, or adapters
- Computer vision experience, especially medical imaging
- Experience with clinical or regulated datasets; HIPAA familiarity
- MLOps experience: model versioning, experiment tracking, monitoring, CI/CD for ML
- Designing AI evaluation benchmarks
- Reinforcement learning or simulation experimentation (Gymnasium a plus)
- OAuth and systems integration patterns; RESTful API design
- Git branching strategies and experience in Scrum/Kanban environments
Benefits
- A core role building real software that eye care practices depend on every day
- The chance to work AI-native — both shipping AI-powered features and using cutting-edge agentic development tooling as part of how we build
- Ownership over meaningful initiatives and a voice in architectural decisions
- A collaborative team at an exciting inflection point
- Professional development opportunities
- Challenging, mission-driven problems in healthcare
Company Overview