Lead AI Engineer

Role - Lead AI Engineer

Experience: 3+ years in AI/ML

Location: Gurgaon, work from office

About Tap Health:

Tap Health is a deep-tech platform that is transforming chronic care management with AI and changing how you access health information. Powered by our proprietary Medical AI model, VaiD, Tap Health is designed to make healthcare accessible to millions.

We are developing next-generation Digital Therapeutic products that redefine chronic illness management through AI-driven, hyper-personalized care. Our platform helps users manage conditions such as diabetes, hypertension, PCOS, pregnancy and asthma by delivering daily structured digital therapeutics, lifestyle interventions, personalized nutrition and exercise guidance and real-time monitoring, all without requiring human intervention.

Leveraging AI and adaptive algorithms, Tap Health dynamically personalizes each user’s care journey, delivering enhanced insights, interventions, motivation, adherence and clinical outcomes at a fraction of traditional healthcare costs.

Beyond Digital Therapeutics, the Tap Health platform also provides free primary illness diagnosis based on symptoms and instant health advice through a seamless, voice-first experience.

www.tap.health

Role Overview: Lead AI Engineer

We are hiring a full-time Lead AI Engineer in Gurgaon to drive AI-driven healthcare innovations.

The ideal candidate has 3+ years of AI/ML experience, 6+ months of GenAI production experience, and 1+ year of hands-on GenAI product development. You need to have a strong data science background and have expertise in GenAI, Agentic AI deployments, causal inference, and Bayesian modeling, with a strong foundation in LLMs and traditional models.

You will be collaborating with the AI, Engineering, and Product teams to build scalable, consumer-focused healthcare solutions. As a Lead AI Engineer, you will be the go-to expert—the engineer others turn to when they hit roadblocks. You will mentor, collaborate, and enable high product velocity while fostering a culture of continuous learning and innovation.

Skills & Experience

The ideal candidate should have the following qualities:

• Strong understanding of fine-tuning, optimization, and neural architectures.
• Hands-on experience with Python, PyTorch, and FastAI frameworks.
• Experience running production workloads on one or more hyperscalers (AWS, GCP, Azure, Oracle, DigitalOcean, etc.).
• In-depth knowledge of LLMs—how they work and their limitations.
• Ability to assess the advantages of fine-tuning, including dataset selection strategies.
• Understanding of Agentic AI frameworks, MCPs (Multi-Component Prompting), ACP (Adaptive Control Policies), and autonomous workflows.
• Familiarity with evaluation metrics for fine-tuned models and industry-specific public benchmarking standards in the healthcare domain.
• Knowledge of advanced statistical models, reinforcement learning, and Bayesian inference methods.
• Experience in Causal Inference and Experimentation Science to improve product and marketing outcomes.
• Proficiency in querying and analyzing diverse datasets from multiple sources to build custom ML and optimization models.
• Comfortable with code reviews and standard coding practices using Python, Git, Cursor, and CodeRabbit.