Curie
Senior AI Engineer
Chicago · Senior
Sponsorship not specifiedDetected 123 days ago
PythonGoPostgreSQLVector DatabasesAWSGCPAzureCloud PlatformsgRPCMachine LearningTensorFlowPyTorchData EngineeringNLPLLMsRAGAgentic AILangGraphAI OrchestrationComplianceDesign SystemsHIPAAHL7/FHIREHR/EMR
About the role
- Improve retrieval accuracy, citation traceability, and relevance ranking to ensure AI-surfaced information is trustworthy and explainable.
- Continuously evaluate and iterate on retrieval quality with structured benchmarks.
- Instrument AI workflows with tracing, logging, and evaluation hooks for compliance-grade visibility into model behavior.
Responsibilities
- Own session and memory management for long-running clinical agents - ensuring continuity, safety, and auditability across patient interactions.
- Extend and maintain the Python service that communicates with other microservices, handling structured clinical data and LLM integrations.
- Build validation layers and guardrails that ensure clinical outputs meet safety thresholds before reaching patients or providers.
- You'll own the Python and Go service layer that powers our clinical AI processing - from multi-step intake reasoning to retrieval-augmented generation for treatment guidance.
- Design systems that respect HIPAA requirements end-to-end - from data handling to model I/O to audit logging.
Requirements
- Strong Python expertise - you're comfortable with async services, and modern tooling (uv, Pyright, etc.).
- Familiarity with PyTorch, TensorFlow, or Hugging Face Transformers for custom model work.
- Hands-on experience with LLMs in production: prompt engineering, structured output, evaluation, and iteration - across commercial APIs (OpenAI, Anthropic, Google) or open-source models (LLaMA, Gemma, etc.).
- Familiarity with agentic AI patterns - multi-step reasoning, tool use, and orchestration frameworks (LangGraph, Google ADK, CrewAI, Claude Agent SDK, or equivalent).
- Comfort working across service boundaries - you can navigate a Go backend, gRPC interfaces, and cloud infrastructure when needed.
- Experience with cloud ML platforms: GCP/Vertex AI, AWS SageMaker, or Azure ML.
- Familiarity with model evaluation frameworks (RAGAS, DeepEval, custom evals) and LLM observability tools (Langfuse, LangSmith, Arize, Weights & Biases).
- Experience with PostgreSQL (including JSONB, pgvector), sqlc, or gRPC/Connect-RPC.
- 7+ years of software engineering experience, with meaningful time building production AI/ML systems.
- Experience building RAG pipelines, vector search, or retrieval systems for grounding LLM outputs - using tools like LangChain, LlamaIndex, or custom implementations.
- Strong intuition for system design that balances correctness, observability, and performance.
- Curiosity about healthcare and a desire to build AI that's safe, explainable, and clinically useful.
- Hands-on with local/self-hosted LLM inference: vLLM, Ollama, TGI, or GGUF-based deployments.
- Fine-tuning or distillation experience - LoRA, QLoRA, RLHF, DPO, or similar techniques.
Skills
- Direct impact on making quality healthcare more accessible.
Compensation
- Competitive salary, significant equity, and benefits in a well-funded company with aggressive growth targets.
Benefits
- Familiarity with healthcare data standards (FHIR, HL7) or EHR integrations.
- Background in medical AI safety, bias detection, or clinical validation.
- Published work or deep domain knowledge in healthcare AI or clinical NLP.
- Shape the AI architecture of a healthcare product from day one - your decisions will directly impact patient care at scale.
- Design and implement multi-step AI agent pipelines that process patient intake, synthesize medical history, and surface clinical recommendations.
- Build and optimize RAG pipelines that ground clinical AI outputs in authoritative medical guidelines, drug references, and treatment protocols - including embedding models, vector stores, and reranking strategies.
Company info
- We're looking for a Senior AI Engineer to design and build the AI systems at the center of Curie's clinical platform.
This listing is sourced directly from Curie's careers page and normalized into a canonical job model.