Software Engineer – Full Stack .NET / AI Developer

Optivate•Bonita Springs, FL

1d•Hybrid

About The Position

About Optivate: Optivate is a leading provider of healthcare technology software solutions purpose-built for ophthalmologists and eye care specialists. The company’s solutions include: Practice management Patient engagement Image management RCM and billing services These tools are designed to: Streamline clinical documentation workflows Improve daily practice efficiencies for eye care professionals About the Role: We’re seeking an 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

Requirements

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
Strong experience with .NET/C# (.NET Core and/or .NET 8+)
Proficiency in HTML/CSS
PyTorch
TensorFlow
Scikit-learn (or similar frameworks)
Embeddings
Vector databases (Pinecone, FAISS, Weaviate)
Semantic search
Deploying AI services using containers, serverless, or managed ML services
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
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 Haves

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

Responsibilities

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
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

Benefits

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

Stand Out From the Crowd

Upload your resume and get instant feedback on how well it matches this job.

Upload and Match Resume