Develop and productionize generative AI applications, including RAG, multi-agent systems, Text2SQL, and fine-tuned models. Own production rollouts, evaluation, and optimization while partnering with product and engineering teams to shape roadmaps. Apply machine learning and data science expertise to business problems, deploy solutions on cloud platforms, and communicate technical concepts to varied audiences. The role also involves collaboration across time zones and may support healthcare and pharmaceutical analytics use cases.

Architects and ships production-grade agentic AI and multi-agent systems for pharmaceutical data, analytics, regulatory, clinical, and medical affairs workflows. Builds RAG pipelines, knowledge graphs, intelligent document processing, observability, evaluation, guardrails, and compliant integrations. Leads AI engineers and ML practitioners, directs architecture, partners with clients on solution delivery, and establishes reusable governance and engineering practices for regulated pharma environments.

Develop scalable full-stack web applications using JavaScript or TypeScript, React, Next.js, Node.js, and Express. Build RESTful APIs and microservices, design and optimize databases, deploy through cloud and CI/CD environments, and apply clean coding, testing, Agile, and code review practices. The role also involves using AI-assisted development tools and collaborating on SaaS, analytics, and healthcare-focused products.