VP of Engineering

Medeloop is redefining clinical operations and health research with a unified AI platform for clinical analytics, study management, and grant automation, streamlining the entire research lifecycle for faster, smarter breakthroughs.

Featured in Politico’s “AI Disrupter-in-Chief” article, Medeloop is trusted by leading institutions across government, academia, and life sciences. At its core is one of the industry's largest and most diverse health data ecosystems, with over 100 million patient records powering AI “scientists” built to drive progress in health equity, drug development, chronic disease, and more.

Backed by world-class investors and led by proven serial entrepreneurs, Medeloop brings together top minds in AI and medical science with a track record of building successful companies. We are not just building technology, we are building a better future for public health.

The Role
We are hiring a VP of Engineering to lead all of engineering at Medeloop during a period of rapid growth and product expansion. This is a high-visibility, high-impact leadership role with the opportunity to take on increasing scope as the company scales.

As VP of Engineering, you will be a key member of the leadership team, working closely with executives to shape strategy and translate it into world-class execution. You will be responsible for scaling a high-performing team, evolving our AI-native infrastructure, and delivering across our core products.

Key Responsibilities

• Partner with the executive team to turn product vision into an actionable technical roadmap
• Scale and structure the engineering team through the next phase of growth
• Own engineering execution across all modules: grants, studies, and analytics
• Define and evolve infrastructure, including agent architecture, data pipelines, and scalability
• Design and operate large-scale data systems that support high-throughput analytics and AI workflows (e.g., Spark, EMR)
• Integrate emerging AI/LLM technologies into the platform
• Ensure ongoing compliance with HIPAA, SOC 2, and data privacy standards

Ideal Background

• Scaled engineering organizations from post Series A through Series B/C and beyond
• Led the development of modular platforms across multiple product lines
• Deep technical fluency in AI/ML, cloud infrastructure (GCP or AWS), and backend systems
• Experience with distributed data processing systems such as Apache Spark on Amazon EMR or EMR Serverless
• Familiarity with agentic architectures and large-scale, data-intensive systems
• Exposure in healthcare and with compliance frameworks (HIPAA, SOC 2) is a plus but not required