Software Engineer .Net/AI Developer

About Optivate Optivate is a leading provider of healthcare technology software solutions purpose-built for ophthalmologists and eye care specialists. The company's solutions, which include EMR, practice management, patient engagement, image management, and RCM and billing services are designed to streamline clinical documentation workflows and improve daily practice efficiencies for eye care professionals. •Applicants must be local OR be willing to relocate to the Bonita Springs area within a reasonable time frame following their start date. Position Summary AI-native Software Engineer with hands-on experience delivering real-world AI-powered products. This role is ideal for a mid-level developer who: Has contributed to 3-5 production AI projects Understands how to move AI systems from prototype to secure, scalable healthcare applications You will: 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 This is not a research-only role. We are looking for someone who has built, integrated, evaluated, and deployed AI systems in production environments.

What You'll Do:

Develop and maintain backend services and APIs using .NET/C# (.NET Core, .NET 8+) Build responsive, user-friendly interfaces using

HTML/CSS

Design AI-enabled workflows that integrate safely into clinical software Collaborate with product, clinical, and engineering teams Establish and participate in code review processes Work within an agile framework, contributing to: Sprint planning Daily standups Retrospectives Write clean, maintainable, testable code Troubleshoot distributed systems and AI pipelines Contribute to architectural decisions around AI infrastructure and model evaluation

AI & Machine Learning Responsibilities:

Design and implement production-grade AI services Integrate third-party

LLMs:

OpenAI Anthropic Azure OpenAI Hugging Face Build and fine-tune ML models: NLP Structured data models Computer vision (where appropriate) Enhance foundation models using: RAG Fine-tuning Embeddings Adapters Design evaluation frameworks to measure: Accuracy Reliability Hallucination rates Clinical relevance Implement retrieval pipelines using vector databases Develop prompt engineering strategies with testing and versioning Optimize model performance, latency, and cost Contribute to reinforcement learning or simulation experimentation (Gymnasium a plus) Collaborate on model deployment, monitoring, and drift detection

Required Qualifications :

3-7 years of professional software development experience Hands-on contribution to 3-5 AI/ML production or near-production projects Experience integrating LLM APIs into real systems Experience building or fine-tuning ML models Experience working with structured and unstructured datasets Strong understanding of model evaluation and production tradeoffs Experience with cloud platforms (AWS, Azure, or GCP) Solid foundation in: Data structures Algorithms APIs Distributed system design

Technical Experience:

Backend Strong experience with .NET/C# (.NET Core and/or .NET 8+) Frontend Proficiency in

HTML/CSS AI/ML

PyTorch TensorFlow Scikit-learn (or similar frameworks) Data Embeddings Vector databases (Pinecone, FAISS, Weaviate) Semantic search Cloud & DevOps Deploying AI services using containers, serverless, or managed ML services

Team & Process Experience:

Experience working in collaborative environments with exposure to: Git version control and branching strategies Agile methodologies (Scrum/Kanban) Task/story management tools Code reviews Architectural discussions Cross-functional collaboration

Mindset & 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 Nice to

Have:

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 Experience with Gymnasium or reinforcement learning Designing AI evaluation benchmarks Understanding OAuth and systems integration patterns Experience with RESTful API design

Knowledge of SQL Server and Entity Framework What We Offer:

Opportunity to build real-world AI products in healthcare Ownership over meaningful AI initiatives Join a growing team at an exciting inflection point Collaborative environment where your architectural input matters Exposure to diverse AI approaches: LLM integration Custom ML Retrieval systems Domain-adapted models Professional development opportunities Work on challenging, mission-driven problems Our Ideal Candidate You've shipped AI features that users rely on.

You understand:

Model limitations Evaluation tradeoffs Production constraints You are: Curious Technically rigorous Thoughtful about AI application in healthcare