Senior AI Engineer

Description

About Rivia

Rivia is a technology company building a data engine that powers the future of clinical trial intelligence. Rivia was founded on the belief that new drugs can be brought to market more successfully with a fraction of today's capital.

Biotechs are the source of most therapeutic innovation, yet clinical development is constantly constrained by fragmented data and outdated tooling. Rivia unifies clinical trial data at scale through a core engine built as a reusable intelligence layer, comprising hundreds of configurations and trial-specific logic, independent of source structure. This vertical stack of data engine, workflows, and agents creates a distinct advantage in how trials are operated.

Over the past two years, European and US based biotechs running global clinical trials on Rivia have demonstrated measurable impact, from earlier understanding of therapeutic potential to significantly more efficient trial execution. In March 2026, Rivia raised its $15M Series A led by Earlybird Venture Capital.

Rivia’s ambition is to become the standard infrastructure for modern drug development, transforming how trials are executed end-to-end.

About AI Engineering at Rivia

Given the highly complex nature of clinical trials and how they interface with our technology, the AI Engineering team at Rivia is pivotal in ensuring our clients achieve their desired outcomes and derive maximum value from our platform.

The team designs and operates agentic, production-grade AI workflows that power critical monitoring, data quality, and insight-generation capabilities for clinical trial stakeholders.​

By building reliable, auditable, and scalable AI systems, AI Engineering helps transform fragmented clinical data into actionable intelligence and positions Rivia as the AI-first platform for clinical trial intelligence.

Responsibilities

• As a Senior AI Engineer at Rivia, you will architect and ship high-impact AI workflows that materially improve how clinical trial teams monitor studies, assess data quality, and make operational decisions.​
• You will work as a key technical contributor embedded in product initiatives, owning AI features end-to-end from design and evaluation through to deployment, observability, and continuous improvement.​
• The ideal candidate is a product-minded engineer who combines deep LLM and agentic systems expertise with strong software engineering skills, a bias to action, and a passion for turning cutting-edge AI into reliable, commercially impactful products in a complex, regulated domain.
• What excites you
• Being part of a collaborative startup where you can make a direct impact on the product, the business, and the team.
• Working in a fast-paced environment where you can leverage your AI engineering expertise to solve complex, real-world problems in clinical trials.
• Building AI systems that customers rely on for critical decisions, where trust, traceability, and auditability are essential.
• Owning outcomes end-to-end, driving clarity, momentum, and quality without heavy oversight, and continuously learning and experimenting in the rapidly evolving LLM landscape.
• Architect and ship production-grade agentic AI workflows, including tool use, orchestration, planning, memory, and structured outputs, for clinical trial intelligence use cases.
• Translate user workflows and product requirements into pragmatic, measurable AI solutions that work reliably in production and optimize for user and business value.
• Design and maintain evaluation pipelines, including gold sets, metrics, and experiments, and use them to drive iteration with rigor.
• Implement robust LLMOps practices, including tracing, monitoring, cost and latency management, safe deployment, and continuous improvement of AI systems in production.
• Design high-quality retrieval and context pipelines with strong guarantees on correctness, provenance, and auditability, particularly in regulated environments such as clinical trials.
• Collaborate closely with Engineering, Product, Design, Sales, and Customer teams to ensure AI features are usable, trusted, and commercially impactful.
• Stay deeply current with the LLM ecosystem, actively experiment with new models and tools, and translate innovation into practical product advantage.
• What Excites us
• Product mindset, with a demonstrated ability to translate user workflows into pragmatic, measurable AI solutions that work reliably in production
• Deep familiarity with the current LLM ecosystem and active experimentation with new models, tools, and techniques.
• Proven experience building and shipping production-grade AI or agentic systems, ideally in high-stakes or complex domains.
• Strong software engineering skills and comfort owning systems end-to-end, from design to deployment and maintenance.
• Experience going from 0→1 at a VC-backed startup or similarly fast-paced environment.
• Hiring Process