Company Description
ClarityCare AI specializes in automating utilization management workflows, including prior authorization, concurrent review, and appeals processes. By integrating directly with your existing systems, ClarityCare reviews clinical documentation, applies plan criteria, and generates auditable determinations with efficiency and accuracy. The company enables healthcare organizations to comply with evolving regulations such as CMS-0057F and state-specific mandates while ensuring effective population management. ClarityCare is dedicated to improving operational workflows and delivering innovative AI-driven healthcare solutions.
Role Description
ClarityCare AI is seeking a full-time Senior AI Engineer to join our on-site team in San Francisco, CA. This is a high-impact technical role at the intersection of applied AI, healthcare infrastructure, and client-facing product delivery. You will architect and build AI-powered systems that automate complex clinical workflows — including prior authorization, utilization review, and determination logic — and deploy them directly into production environments at health plans, TPAs, and medical management companies.
Day-to-day responsibilities include designing LLM-powered pipelines, building robust back-end services, scoping and delivering integrations with enterprise health systems (FHIR, HL7, EDI), and working closely with the product and customer success teams to translate clinical and regulatory requirements into scalable software. You'll operate with significant ownership and autonomy, and your work will directly shape the core product.
Qualifications
- 5+ years of software engineering experience, with at least 2 years focused on AI/ML systems in production
- Deep experience designing and deploying LLM-based applications, including prompt engineering, RAG pipelines, fine-tuning, and evaluation frameworks
- Strong back-end engineering skills in Python; experience with FastAPI, async architectures, and cloud infrastructure (AWS/GCP/Azure)
- Experience integrating AI systems into complex enterprise environments with strict compliance and audit requirements
- Strong communication skills; comfortable working directly with clients and non-technical stakeholders to scope and validate solutions
- Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field; advanced degree a plus
Tech stack
We use all the following technologies. Your knowledge of these would be helpful, but you don’t need not be familiar with all of them as we assume you’re smart enough to pick up anything quickly.
- Cloud - AWS: ECS, Lambda, SageMaker, RDS, Bedrock, Temporal
- Backend - Python: PostgreSQL, FastAPI, GitHub, Terraform, Logfire (OpenTelemetry)
- Frontend - Typescript: React, Vite, Next, Shadcn
- Machine Learning
- NLP: graphRAG, RAG, prompt engineering, fine-tuning, spaCy, MedBert
- CV: VLLMs, multimodal embeddings (ColPali)
- Open source LLMs: Bert-based models, Meditron
- Document intelligence: OCR
