Software Engineer – Full Stack .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 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

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