Patient safety is entering the AI era.
Better systems, deeper intelligence, and enduring respect for scientific
judgment. These will define what comes next.
Every enduring system begins with the questions it refuses to ignore.
Patient safety software doesn’t simply support decisions. It shapes them.
Every workflow, every field, every interruption influences how experts think,
review and decide.
That’s why we treat interface design as part of the safety system, not
decoration around it.
No single discipline can redesign patient safety. Product designers, AI researchers, pharmacovigilance specialists, engineers and clinicians work as one team to approach the same problem from entirely different, and much required, directions.
A designer questions whether the interface creates the right kind of confidence. An engineer asks whether the system can be trusted under pressure. A researcher asks whether the model’s reasoning is sound. A safety scientist asks whether the output reflects what the evidence actually shows.
Each brings a distinct form of scrutiny. None of them is sufficient alone.
The tension between perspectives is not a problem to be managed. It is where the best thinking happens.
Science · Product · Design · Engineering · AI
Patient safety is too complex for any one discipline to solve alone. At Graph, science, product, design, engineering and AI come together around the same problem — and stay close to it.
01
The problem comes first. Expertise follows it. We bring different ways of seeing the same problem into the room, because the strongest solutions rarely belong to one discipline.
02
Good ideas are not protected here. They are tested. We challenge assumptions, expose gaps and change direction when the evidence tells us to.
03
We don’t throw work over the wall and hope it survives. We explain our thinking, share context early and make decisions others can build on.
04
What we build ultimately supports decisions that matter to patient safety. That keeps the details important — and keeps us connected to why they matter.
2+ years | Global / Multiple time zones | Hybrid / On-site | Full-time
Help customers get the most out of our Pharmacovigilance SaaS platform by investigating issues, resolving product questions, and providing thoughtful support. The role involves working across teams and channels to understand customer needs, drive issues through to resolution, and deliver a strong support experience.
2+ years | Global / Multiple time zones | Hybrid / On-site | Full-time
3–5 years | Hyderabad, Telangana, India | In-office | Full-time
Build and maintain robust, scalable applications that support Graph AI’s Pharmacovigilance Safety Product Suite. The role spans the full development cycle, from intuitive React interfaces to backend services and APIs, while working closely with product and AI teams
3–5 years | Hyderabad, Telangana, India | In-office | Full-time
3–8 years | Hyderabad, India | On-site | Full-time
Keep Graph AI’s internal technology environment secure, reliable, and running smoothly across infrastructure, enterprise applications, endpoints, and cloud services. You’ll work across IT operations, security, compliance, and automation to support the organization’s day-to-day technology needs.
3–8 years | Hyderabad, India | On-site | Full-time
10+ years | Greater NY / NJ / Boston / PA Hub | Remote | Full-time
Drive Graph AI’s growth across the pharma and life sciences industry by bringing an AI-native approach to pharmacovigilance to enterprise customers. This role owns the full sales cycle, building relationships with senior decision-makers and guiding complex deals from discovery through contract.
10+ years | Greater NY / NJ / Boston / PA Hub | Remote | Full-time
15+ years | Greater NY / NJ / Boston / PA | Remote | Full-time
Shape how the world sees Graph AI — from its brand and story to the demand engine that turns awareness into enterprise pipeline. As the first VP of Marketing, you’ll define the marketing strategy, build a distinctive market identity, and lead a high-performing team across global markets.
15+ years | Greater NY / NJ / Boston / PA | Remote | Full-time
4–8+ years | Hyderabad, Telangana, India | Full-time
Shape the quantitative science behind Graph Safety’s signal detection, risk management, and therapeutic analytics. This role brings together statistical methods, real-world evidence, and pharmacovigilance expertise to build explainable, auditable safety intelligence across the full lifecycle of a molecule.
4–8+ years | Hyderabad, Telangana, India | Full-time
4–6 years | Hyderabad, Telangana, India | In-office | Full-time
Ensure the Graph Safety Product Suite delivers reliable, high-quality experiences across features, AI model updates, and bug fixes. You’ll combine manual and automated testing to validate full-stack applications while maintaining the quality and compliance expected in a regulated GxP environment.
4–6 years | Hyderabad, Telangana, India | In-office | Full-time
2–5 years | Hyderabad, India | Full-time
Support customers using Graph AI’s Pharmacovigilance and Drug Safety solutions, helping resolve application issues and keeping incidents moving toward resolution. The role combines technical troubleshooting, functional guidance, and close coordination with internal teams to deliver a reliable customer experience.
2–5 years | Hyderabad, India | Full-time
The future belongs to people who care deeply about
scientific thinking, thoughtful design, and systems
worthy of the decisions they support.
Are you excited to build the Intelligence
infrastructure for modern patient safety?
