Senior Applied AI Engineer

Konovo is a global healthcare intelligence company on a mission to transform research through technology- enabling faster, better, connected insights.

Konovo provides healthcare organisations with access to over 2 million healthcare professionals—the largest network of its kind globally. With a workforce of over 200 employees across 5 countries: India, Bosnia and Herzegovina, the United Kingdom, Mexico, and the United States, we collaborate to support some of the most prominent names in healthcare. Our customers include over 300 global pharmaceutical companies, medical device manufacturers, research agencies, and consultancy firms.

As we transition from a service-oriented model to a product-driven platform, we are expanding our hybrid Bengaluru based team. We are looking for a Lead Applied AI Engineer to help advance the next chapter of Konovo’s AI-native platform.

AI is already embedded in our product and internal tooling. Your role will be to deepen, scale, and operationalise those capabilities across our platform, data systems, and engineering workflows with production reliability and enterprise discipline. You will partner with global engineering, data, and product teams to translate real business problems into production-ready AI solutions.

This is a hands-on role for someone who understands both the promise and limits of modern AI. You will design thoughtfully, build pragmatically, and ship responsibly. Your work will directly shape how our customers and employees experience AI at Konovo. You will operate in an environment where AI decisions impact enterprise customers globally and must meet high standards of reliability, compliance, and performance. AI is a strategic differentiator for Konovo. As a globally scaled healthcare intelligence company service hundreds of enterprise customers, AI at Konovo must accelerate innovation while protecting reliability, data integrity, and customer trust.

How You’ll Make an Impact:

• Design, build, and deploy production-grade AI and LLM-powered features within our intelligent platform
• Improve model performance, reliability, observability, and cost efficiency in enterprise-scale production environments
• Collaborate with product and engineering teams to translate business requirements into scalable AI solutions
• Advance our provider-agnostic AI architecture to enable secure access to multiple LLM ecosystems
• Build internal AI tooling that enhances engineering productivity and broader employee workflows
• Establish best practices for model evaluation, prompt engineering, testing, and governance
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