AI Engineer

As an AI Engineer, you will join our world‑class engineering team in building the Verisian Platform. You will use the latest in AI, specifically LLMs and RAG systems, in combination with Verisian’s game‑changing code and data traceability to create the world’s best Coding Agents, Analysis/Results Validation Agents, Submission Documentation Agents, and Onboarding/QA/Exploration Agents.

The Verisian Platform brings value to a set of highly regulated processes crucial for medical progress and innovation. You will be working on the Planner, Builder, Explorer, Validator, Submitter, and related supporting modules. These core modules of the platform target the planning, exploration/onboarding, building, validation, submission, and review of clinical trials and their results. They enable data managers, statistical programmers, statisticians, medical writers, and regulators to deliver their work faster, at higher quality, lower cost, and in greater confidence.

Our pipelines analyze clinical trial documentation, code, logs, data, and results to build a knowledge graph through code traceability. We harness the resulting dataset, column‑level and logic lineage to turn clinical trials into Information Infrastructure that can be used by experts and consumed by AI to revolutionize how therapies are evaluated and enter the market. We capture complex processes in fully‑ and semi‑automated workflows that place experts in control and AI automation at their fingertips. We build visualizations to provide our customers with a maximum of insight as fast as possible.

Our application stack is based on Next.js and deployed via Docker/Kubernetes in the cloud. The data analysis pipelines run in Argo Workflows. We analyze code based on Antlr4 and Java. AI agents are developed in Python. The data analysis engine is developed in Python. Git is where our code lives, and Github Actions is how it gets out into the world.

You will be expected to lead the analysis, design, and engineering of our AI stack (RAG system, selection and fine‑tuning of models, production deployment), develop strategies for development, regression testing, training/validation data and associated benchmarks, and contribute to its production‑ready deployment. As part of our core team, you will join us in designing, prioritising, building and testing new functionality, troubleshooting customer issues, finding root causes, and developing improvements to ensure maximal user impact and performance.

Analysis/Results Validation Role

This role will focus on the Verisian Agentic AI Validation. You will use specifications, code, data, and documentation from existing trials accessible, pre‑structured, and consumable through our APIs to build agents that test if the data and statistical results are calculated according to their specifications. Verisian’s code traceability allows for the retrieval of exactly and only those lines of code required to derive specific variables/outputs, providing the perfect context for comparing the implementations in code to their natural language specifications, no matter the size of the code base. The agents will report differences between specification and implementation and make suggestions for how to fix them to ensure an integral analysis and subsequent submission.

Submission Documentation Role

This role will focus on the Verisian AI Submissions Agents. You will use specifications, code, data, and documentation accessible, pre‑structured, and consumable through our APIs to build agents that create drafts and improve the editing of crucial submission documentation. These documents describe datasets, their contained variables, their use in statistical tests, as well as the produced results. They also help guide reviewers through the complexities of trials and highlight the most important parts of a submission and outline patient journeys through the trial. Verisian’s code traceability allows for the retrieval of exactly and only those lines of code required to derive specific variables/outputs as well as connected data on the level of individual patients through time. This means our agents can retrieve the perfect integrated context to document implementations and statistical models, no matter the size of the code base. This solves one of the fundamental problems of modern AI systems: high accuracy and fidelity even as complexity and size increase.

Qualifications

• Experience with and foundational understanding of LLMs (especially open source models), including production deployment
• Experience with and foundational understanding of non‑LLM AI, including production deployment
• Experience with RAG systems
• Strong interest in programming languages, parsing algorithms, interpreters, and compilers
• Strong interest in understanding data science and statistical analyses
• Extensive experience in Python, Pandas, and at least one other programming language
• Highly motivated and highly independent, able to create and manage a code base
• Strong focus on building as a team: we have a We & Mission mindset
• Strong ability to communicate complex technical problems and solutions, foresee risks, and align work across multiple teams and colleagues
• “If it’s not code and documented, it doesn’t exist” mindset
• Iteration mindset

Bonus Points for

• Experience with code generation/validation/analysis
• Experience in data/statistical analysis
• Experience in clinical trials

Benefits

• What you build impacts billions of people around the world
• Highly collaborative, ambitious and world‑class team
• Employee Stock Options Plan
• All remote, asynchronous work environment with in‑person summits around the world
• Pension plan and additional benefits depending on country of residence