Generative AI Engineer

About the Company

AppifyTech is a product-based company focused on providing cutting-edge AI-powered healthcare solutions in the US market.

About the Role

We are looking to hire an experienced GenAI Engineer with a Computer Science degree who has pivoted to GenAI solutions since the inception of ChatGPT and has hands-on experience delivering production GenAI applications.

Key Responsibilities & What We Offer

• Develop and deploy production GenAI solutions for healthcare applications including medical coding, clinical documentation, and healthcare automation

• Work with state-of-the-art GenAI technologies: OpenAI GPT models, Anthropic Claude, and Google Gemini

• Build multi-agent systems and complex GenAI workflows using modern AI frameworks

• Collaborate in an environment that encourages entrepreneurial thinking in the rapidly evolving AI landscape

• Lead innovative GenAI initiatives aligned with healthcare transformation goals

• Gain valuable US healthcare domain expertise - an extremely valuable and highly paid domain with massive GenAI opportunities

• Participate in the challenges and growth opportunities of an AI-first product company

• Receive candid feedback and exposure to the latest GenAI research and applications

Qualifications

• Experience: 5+ years of overall software development experience with minimum 3 years focused on GenAI solutions

• GenAI Transition Story: You must have prior software development experience but have pivoted to GenAI solutions in the last 2-3 years (since ChatGPT's launch)

• Production GenAI Experience: You've delivered at least one significant project that involved either:

Integration of GenAI capabilities into existing enterprise software, OR

Built a GenAI application from scratch that reached production users

• Multi-Model Expertise: Hands-on experience with OpenAI, Anthropic Claude, and Google Gemini models in production environments

• LLM Frameworks: Experience with LangChain/LangGraph, DSPy, or other agentic frameworks for building complex GenAI workflows

Required Skills

GenAI & AI Systems:

• Advanced prompt engineering and multi-agent system design

• Experience with structured outputs, function calling, and RAG implementations

• Knowledge of GenAI observability, caching, and fallback strategies

• Understanding of multimodal AI (text + images/documents)

• Python expertise with Django/FastAPI for GenAI APIs

• Experience with vector databases and semantic search

Traditional Tech Stack:

• Strong foundation in LAMP stack (Linux, Apache, MySQL, PHP) or equivalent

• Experience with web frameworks like CakePHP, Laravel, CodeIgniter, or similar

• Proficiency with MySQL/MariaSQL, including optimization and scaling

• Knowledge of caching solutions (Memcached, Redis)

• Message queue systems (RabbitMQ, Celery, or similar)

• Understanding of traditional web architecture and database design

Professional Qualities

• Finisher - GenAI projects require going the extra mile to handle edge cases, model failures, and user experience nuances

• Commitment - Own your GenAI deliverables and collaborate to solve complex AI challenges

• Team first - Put product success over individual AI model preferences or technical ego

• Adaptability - GenAI landscape evolves rapidly; you must stay current and adapt to new models/techniques

• Problem solving - Healthcare + AI brings unique challenges requiring creative technical solutions

• Ethics & Safety - Understanding of responsible AI practices, especially in healthcare contexts

You must be an excellent AI Engineer (not just a prompt writer) with deep understanding of modern GenAI architectures, healthcare workflows, and production AI system design.

Preferred Skills

• Healthcare/medical domain knowledge

• Experience with medical coding (ICD-10, CPT), clinical documentation, or healthcare automation

• Knowledge of HIPAA compliance for AI systems

• Experience with document AI, OCR, or medical image processing

When applying, please mention:

1. Your specific GenAI transition story (what you built before vs. after ChatGPT)

2. Details about your production GenAI project(s)

3. Which LLM models you've worked with in production and for what use cases

4. Your area of expertise within the GenAI ecosystem