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