AI Engineer

at HapiVet AI

AI Engineer

HapiVet AI

Company

Home

AI Engineer

at HapiVet AI

Posted by Vikram P

3 - 6 yrs

₹5L - ₹35L / yr

Hyderabad

Skills

Generative AI

Natural Language Processing (NLP)

Retrieval Augmented Generation (RAG)

Large Language Models (LLM)

PyTorch

TensorFlow

Key Responsibilities:

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
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.

Key Responsibilities:

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
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.

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About HapiVet AI

Founded :

2025

Type :

Services

Size :

0-20

Stage :

Raised funding

About

N/A

Company social profiles

N/A

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