AI Engineer

Client Background Our client is a healthcare technology company building an AI-driven platform that augments medical expertise with large-scale research synthesis and long-term personalization. Their focus is on creating safe, traceable, and deeply human-centered AI systems that support clinicians in delivering better outcomes over decades, not just point-in-time recommendations.

The Mission Even the best doctor cannot read every research paper published today. Your job is to build the AI system that turns a great doctor into a Super Doctor. You will build the intelligence layer that synthesizes massive health datasets into actionable, traceable, and personalized advice.

The Challenge This is not a generic chatbot. It is a high-stakes health advisor. You will solve for traceability, explaining why the AI suggested a recommendation, and hyper-personalization, showing how specific research applies to a specific client’s biology. You will create feedback loops that allow practitioners to validate hypotheses and evolve a client’s health plan over decades.

What You’ll Do Synthesize Knowledge: Build retrieval-augmented generation systems, agentic workflows, and fine-tuned models that ingest medical research and map it to individual client profiles. Traceability and Safety: Ensure every AI-driven recommendation is backed by data and can be verified by a human expert. Feedback Loops: Create systems that learn from client progress and continuously adjust health goals based on real-world outcomes. Operational Intelligence: Streamline the health concierge workflow so experts can focus on relationships while AI handles knowledge synthesis and analysis.

Who You Are You understand that AI in healthcare is a matter of hypothesis and validation. You are a researcher-builder motivated to create AI systems that meaningfully extend human health and longevity, not simply generate text.

Required Skillset The client is open to both Junior (Fresh Graduate) and Senior (5 or more years of experience) candidates who possess:

CS Fundamentals: A Computer Science degree or equivalent deep technical understanding of AI fundamentals. AI and ML Experience: 3 to 4 years of experience in AI or ML development, with a focus on knowledge synthesis, verification, and contextualization using LLMs or other models. Datasets and Evaluations: Experience creating evaluations using synthetic datasets and human feedback when gold-standard datasets are not readily available.

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