We are hiring a Senior AI/ML Engineer to own the end-to-end applied LLM, retrieval, and evaluation layer of our healthcare AI platform. You will build production systems that automate mid- and end-revenue cycle workflows for US healthcare spanning coding, claim edits, denials triage, appeal generation, and payer-rule reasoning.

This is a production engineering role (not research) focused on building scalable, auditable, and cost-efficient LLM systems in a regulated healthcare environment.

What Were Looking For :

Must-Have :

- 5+ years in ML/AI engineering, including 6+ months in production LLM systems

- Hands-on experience deploying and operating self-hosted LLMs (vLLM, SGLang, TensorRT-LLM, or equivalent)

- Strong experience designing embedding-based retrieval and/or knowledge graphs for grounded LLM applications

- Demonstrated ownership of evaluation infrastructure - offline benchmarks, online monitoring, drift and regression detection

- Strong Python + PyTorch + Hugging Face experience

- Production experience with monitoring, incidents, and system ownership

Strongly Preferred :

- Fine-tuning experience (SFT, LoRA, QLoRA, DPO) on domain-specific corpora

- Experience with graph databases (Neo4j, ArangoDB, or equivalent) and graph-aware retrieval

- Experience with vector databases and hybrid search (BM25 + dense, rerankers)

- Familiarity with LLM observability tools (Langfuse, LangSmith, Arize, Braintrust, or in-house equivalents)

- Exposure to healthcare, RCM, claims, or other regulated domains

- Experience with MCP or similar tool-orchestration frameworks

- Strong prompt-engineering and LLM-evaluation instincts