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Build AI-powered features and products for clinical documentation and medical coding. Develop LLM-driven agentic systems, APIs, services, and production infrastructure across healthcare revenue cycle workflows. Create evaluation frameworks and experimentation loops using statistical and data-driven methods to ensure reliability, auditability, and alignment with coding guidelines and user feedback. Collaborate with product, design, machine learning, clinical, and revenue cycle experts to deliver high-impact SaaS solutions.

Leads customer implementation pods from contract signature through deployment and post-implementation support. Manages 6–8 concurrent software projects, coordinating cross-functional teams, timelines, risks, dependencies, communications, and status reporting. Uses internal dashboards to demonstrate customer ROI and monitor product health. The role requires enterprise client-facing experience, technical implementation expertise, creative problem-solving, and strong organizational and communication skills. It is based in the San Francisco Bay Area or New York City with 2–3 in-office days weekly and minimal occasional travel.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.

Sell AKASA's AI-native revenue cycle management solutions to health systems. Build C-level relationships, drive business development, lead full sales cycle from prospecting to close, deliver consultative presentations, work with BDRs, attend industry events, and collaborate cross-functionally. Travel domestically up to 60%.

Own and lead a flagship clinical documentation and medical coding product within an AI-native suite. Define strategy, evaluate opportunities, create roadmaps and PRDs, and drive execution with engineering and ML teams. Partner with customers, design partners, and cross-functional teams to launch, measure, and iterate on products that improve documentation quality and revenue cycle outcomes.

Lead and scale AKASA's compliance and AI governance: own HITRUST, SOC 2, and HIPAA programs; operationalize NIST AI RMF; drive automation-first GRC and continuous control monitoring; manage policy lifecycle, vendor risk, customer audits, and sales security support; partner with Engineering, Legal, and Security.

As a Sr. Software Engineer, Backend, you will develop AI-powered solutions for clinical documentation and medical coding, collaborating with cross-functional teams to enhance SaaS products and deliver actionable insights for healthcare organizations.

Deploy and maintain ML/LLM models for healthcare revenue cycle clients: handle implementation from requirements through rollout and production support, run LLM evaluation frameworks, integrate data pipelines and databases, and collaborate with client engagement, product, and R&D teams to improve platform performance.