Engineering Internship

Tandem
New York officePosted 23 January 2026

Job Description

Why you should join usTandem is a generational opportunity to rethink how we bring new therapies to market, and our path to doing so is significantly de-risked – we have:Exponential organic growth: We have product-market fit and are growing rapidly. Tandem supports thousands of new patients every day, is spreading with doctors through word-of-mouth, and works with the largest biopharma companies in the world.An AI-first business model: Our approach is distinctly enabled by AI, but our business gets stronger (not commoditized) as foundation models improve. We are building durability through two-sided network effects that compound over time.Top tier investors: With the traction to support conviction in our model, we raised significant funding from top investors (Thrive Capital, General Catalyst, and Accel) to build an exceptional team of engineers and operators.Our number one priority is scaling to market demand. We are looking for individuals who are high horsepower, high throughput, and hyper resourceful to help us increase capacity and grow. We move fast and need to move faster.All full-time roles are in person in New York. You can learn more about working with us in the last section of this page.About the roleWe are looking for full-stack and platform engineering interns who want to work on real production use cases of LLMs and help us scale to consumer and physician demand. You will take on a specific business problem and lead the prototyping, evaluation, and product integration of AI-powered solutions. Your responsibility will include exploring both established and emerging methods and determining what gets us to the best outcome. You will be expected to drive your project independently, but you will work closely with individuals on our Engineering, Data, GTM, and Operations teams to work through key decisions, get feedback, and launch your features.Summer internships are full-time at our office in NYC. In addition to working as part of our Engineering team, you will have the option to spend a portion of your time shadowing or working on a GTM-focused project with our GTM team or CEO.We are flexible on start date, with potential to extend beyond the Summer into the Fall semester.We need your help to:Decipher and automate complex, branching workflows for insurance coverage, affordability programs, and fulfillmentCombining AI/ML approaches to achieve high precision document classification, unstructured data extraction, and reference-based question answeringAutomating multi-step, path-dependent processes, using a combination of RPA/scraping approaches to navigate and operate third-party platformsBuilding a state machine that drives system decisions and handles failure modes across a set of processes that are technically independent but practically intertwinedScale across a growing range of drug classes, patient populations, and provider marketsMaking our data and ML pipelines robust to variation and inconsistency in input data formats (e.g., clinical documentation structure and style)Leveraging empirical data to build and continuously update our understanding of opaque external systems (e.g., insurance company policies)Creating consumer-grade experiences for patients, physicians, and other users that incorporate intuitive AI-powered workflowsUse our network to help biopharma partners accelerate drug development, launch, and accessTranslating large volumes of heterogeneous data into reliable insights, informing decisions like clinical indication selection, launch markets, and insurer negotiationsDeveloping predictive and simulation models to forecast outcomes such as clinical trial site performance, drug adoption rates, and the impact of rebates/subsidiesUsing real-time data and direct engagement channels to enroll criteria-matching patients and physicians in clinical studies and access programsWe’ll be most excited if you have:An expected graduation date between 2027-2029 with a Bachelor’s degree (or higher) in Computer Scien ... (truncated, view full listing at source)
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