Forward Deployed Engineer

About AKASA At AKASA, our mission is to build the future of healthcare with AI. As the leading provider of generative AI solutions for the healthcare revenue cycle, we help health systems comprehensively capture and communicate the full patient clinical journey. By empowering health systems to streamline their operations, they can focus on what matters most - delivering quality patient care. We have raised over $205M in funding from investors such as Andreessen Horowitz, BOND, and Costanoa Ventures. This is the most exciting time to join AKASA. Revenue bookings for our new AI-native product suite have grown over 20x since launching in 2024. In this time, we have broken our record for the largest deal in company history three times consecutively. This growth is driven by the massive improvement we are generating for our customers across clinical quality and documentation accuracy, both top priority areas for health system leaders. Our deployments have been recognized nationally as "one of the most comprehensive real-world uses of GenAI in healthcare finance to date" (link). Our customer base represents more than $120B+ in net patient revenue and includes the most innovative health systems in the country, like Cleveland Clinic, Duke, Stanford, and Johns Hopkins. Some of our recent recognitions include being named one of America's Top Startup Employers 2026 by Forbes, #1 most [... source excerpt omitted ...] to redefine what’s possible in healthcare. We’re looking for exceptional people to help us accelerate that reality. About the Role As a Forward Deployed Engineer, you’ll deliver client deployments that empower healthcare revenue cycle teams to work faster, more accurately, and with greater insight. You will work on the lifecycle and deployment of the ML models that power our products. You’ll work closely with client engagement, product, and R&D teams to ensure smooth deployments, ongoing production stability and expansion of our deployment platform. What You'll Do Execute implementation tasks for new deployments — from requirements analysis to configuration, testing, rollo [... source excerpt omitted ...] ough technical onboarding, integration setup, troubleshooting, and data acquisition Build and own evaluation frameworks to continuously measure and improve LLM performance across customer deployments Contribute feedback and insights that shape product and platform improvements Work closely with R&D engineering teams to build robust scalable client solutions Skills & Qualifications Bachelor's degree in Computer Science, Engineering, or similar 3+ years of professional Python experience Experience designing and running LLM evals (offline and online) to measure model quality and performance. Comfortable working with relational databases, APIs, and ETL pipelines Strong commu