- Design AI-driven solutions for core veterinary workflows, such as patient triaging, diagnostics support, treatment plan suggestions, appointment scheduling, and client communications.

- Develop AI assistants and multi-agent systems to automate routine tasks like SOAP note summarization, clinical documentation (Medical Records), prescription and other reminders, and client follow-ups.

- Implement RAG pipelines leveraging veterinary knowledge bases, clinical case data, Case Summaries and standard care protocols.

- Integrate LLMs into practice management modules for intelligent querying, FAQ automation, and veterinary clinical knowledge support.

- develop and deploy AI services using Azure AI Services, Azure OpenAI, and integrate with Hapivet.ai

- Ensure secure, compliant, and scalable deployment of AI/ML models in line with veterinary data privacy standards and healthcare regulations.

- Collaborate with veterinarians, product managers, and software engineers to ensure AI solutions are clinically relevant, user-friendly, and impactful.

Required Skillset :

Machine Learning & Deep Learning for Healthcare :

- Strong foundation in supervised/unsupervised learning, anomaly detection, and predictive analytics applicable to veterinary clinical data.

- Experience with CNNs (for imaging), RNNs/LSTMs (for sequential data like patient histories) and Transformers for natural language tasks.

- Proficiency with TensorFlow, PyTorch, and Hugging Face.

- Good to have understanding on GANs (medical imaging, data privacy-safe synthetic data, or image-based diagnostics)

LLMs & NLP for Veterinary Applications :

- Deep understanding of transformer models (GPT, BERT, LLaMA) applied in medical/veterinary text summarization and knowledge extraction.

- Fine-tuning LLMs with techniques with PEFT, LoRA, QLoRA for domain-specific tasks.

- Expertise in Prompt Engineering and Chain of Thought (CoT) design for veterinary use cases.

- RAG pipeline development with veterinary case databases using Pinecone or Azure AI Search.

AI Agent Workflows & Orchestration :

- Multi-agent coordination and AI workflow orchestration with LangChain, LangGraph, and Microsoft Autogen SDK.

- Experience with context management using Model Context Protocol (MCP) in clinical task flows.

Cloud AI Deployment & Engineering

- Experience with Azure AI, model serving (Triton, TensorFlow Serving, TorchServe).

- CI/CD for AI models, cloud security, and scalable API integration.

Programming & Data Engineering :

- Advanced proficiency in Python, R , Agentic AI.

- working knowledge of TypeScript.

- Veterinary data processing experience-handling EMRs, patient histories, and diagnostic reports

- Data cleaning, transformation, and ensuring data quality for clinical applications.

Preferred Experience :

- AI/ML deployment in veterinary practice management systems or healthcare applications.

- Understanding of veterinary compliance, data sensitivity, and client confidentiality (e.g., pet health records, veterinary licensing).

- Exposure to veterinary-specific AI applications, such as diagnostic imaging analysis, clinical decision support systems, or client interaction bots.

- Familiarity with DeepSpeed, Megatron-LM, and scaling techniques for LLMs.

Soft Skills & Domain Understanding :

- "Passion for improving pet care and veterinary services through technology".

- Strong communication skills for collaborating with veterinary professionals.

- Ability to translate clinical workflows into AI-enabled solutions.