Teams at Redica Systems

Leads and develops scalable data pipelines, APIs, microservices, and ETL/ELT systems for regulatory and health agency datasets. Ensures data quality through automated testing, monitoring, and validation; integrates pipelines with NLP, machine learning, and search services; and supports production incident resolution. Mentors junior and mid-level engineers, establishes technical standards, conducts code reviews, and translates architecture and product requirements into actionable engineering work.

Build and deploy production-grade AI applications using LLMs, generative AI, conversational and agentic frameworks. Develop Python and FastAPI backend services, scalable microservices, hybrid search using vector and graph databases, and integrations with data pipelines and platform APIs. Maintain AI systems in production, including testing, monitoring, troubleshooting, and performance optimization while collaborating with product and engineering teams.

Develop and maintain scalable AI and ML architectures for a life sciences regulatory intelligence platform. Lead technical decisions, integrate LLM services and microservices, build conversational and agentic systems, manage data stores and databases, support production delivery, and collaborate in an Agile Scrum environment. The role requires hands-on Python development, generative AI deployment, cloud architecture, vector and graph databases, hybrid search, and backend API development.