Senior Software Engineer, AI – Backend

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Nexleaf Analytics

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2015

⚕️ Healthcare Insurance

Healthcare Insurance • Internet of Things • Data

Nexleaf Analytics is a company dedicated to accelerating digital transformation in health systems through holistic interventions that include IoT solutions, data tools, and workforce development. The company equips health workers with the necessary data, skills, and tools to keep medical equipment operational, optimize supply chains, and save lives. Nexleaf's flagship technology, ColdTrace, provides continuous data from health facilities and refrigeration equipment to support vaccine protection. They operate in over 30 countries, working closely with health systems to foster a culture of data-driven decision-making. Nexleaf's solutions focus on key areas such as ensuring reliable electricity and safeguarding medical equipment for the delivery of lifesaving care.

📋 Description

• Architect and ship AI-driven features — RAG pipelines and agentic workflows that take action across systems with human oversight where it matters. • Build the backend and infrastructure to run these reliably and at scale, across tens of thousands of IoT devices and low-connectivity environments. • Define what "good" looks like for our AI systems — holding them to real accuracy and impact standards, not demo performance. • Own large parts of the system end-to-end, from architecture to production reliability. • Work closely with product and data science to iterate fast and keep solutions aligned with product vision and real public-health needs.

🎯 Requirements

• Expert-level Python and backend engineering, with a track record of scalable production services. • Proven, in-production experience with RAG (retrieval, embeddings, vector stores). • Hands-on experience building agentic systems — multi-step, tool-using AI that takes action, not just chat. • Strong grasp of the infrastructure to run AI in production reliably at scale (cloud, AWS/GCP). • Demonstrated experience evaluating AI systems for accuracy and real-world impact, and iterating on results.