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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer .Net/AI Developer - **Company:** OPTIVATE HEALTH, LLC - **Location:** Bonita Springs, FL, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** .NET Framework, Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Computer Vision, Automated Storage and Retrieval Systems, Microsoft Azure, C Sharp (Programming Language), Clinical Data Repository, Code Review, Continuous Integration, Data Structures, DevOps, Distributed Systems, Entity Framework, Machine Learning, OAuth, Scrum Methodology, Tensorflow, Azure Machine Learning, Search Technologies, Software Engineering, Unstructured Data, Management of Software Versions, AI Infrastructure, Reinforcement Learning, .NET Core, Pytorch, Large Language Models, Model Validation, Backend, Git, AI Platforms, Git Flow, Scikit Learn, HuggingFace, Machine Learning Operations, Front End Software Development, Restful APIs, Software Version Control, Serverless Computing - **Published:** May 14, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=edfce54db2314bf5 ## About the Role Do you have experience in Version control?, * 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 ## Description 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, * 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 ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Keeping applications secure by evolving OAuth 2.0 and OpenID Connect](https://www.wearedevelopers.com/videos/100152-keeping-applications-secure-by-evolving-oauth-2-0-and-openid-connect) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Developer Experience, Platform Engineering and AI powered Apps](https://www.wearedevelopers.com/videos/990-developer-experience-platform-engineering-and-ai-powered-apps) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## Related Articles - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)