Staff AI Engineer

Staff AI Engineer

At ModMed, we are on a mission to place doctors and patients at the center of care through an intelligent, specialty-specific cloud platform. We envision a world where our software increases medical-practice success and improves patient outcomes.

We don't just build code; we innovate boldly to save time for healthcare providers so they can focus on what matters most. If you want to align your passion with purpose and use AI to do good in the world, you belong here.

The Opportunity

Staff AI Engineer

technical leader and hands-on engineer

How You’ll Make an Impact

• Architect AI Innovation:

  Design and build scalable, production-grade

  LLM, Generative AI, and Agentic AI solutions

  that solve complex healthcare and medical-practice workflows.

• Build AI Systems End-to-End:

  Lead the architecture and implementation of

  RAG pipelines, AI agents, orchestration, tool calling, document intelligence, and intelligent automation

  from prototype through production.

• Engineer for Reliability:

  Establish robust approaches for

  LLM evaluation, grounding, guardrails, observability, security, latency, and cost optimization

  to ensure AI systems are reliable and production-ready.

• Solve Complex Problems:

  Apply advanced

  prompt engineering, model selection, fine-tuning, retrieval strategies, and ML techniques

  to address specialty-specific healthcare challenges.

• Drive Technical Excellence:

  Define reusable AI engineering patterns, architecture standards, and best practices that can be adopted across ModMed's AI initiatives.

• Lead Without Authority:

  Partner with Product, Engineering, Data Science, and domain experts to influence technical direction, make architecture decisions, and drive successful delivery of high-impact AI initiatives.

• Mentor & Multiply:

  Mentor senior and junior engineers, conduct technical design reviews, and raise the engineering and AI maturity of the broader organization.

• Innovate Responsibly:

  Help ensure AI solutions are

  secure, explainable, governable, and appropriate for healthcare

  , with strong attention to privacy, compliance, and responsible AI practices.

What You Bring to the Team

The Essentials:

• Experience:

  10+ years of experience in AI/ML, Machine Learning, Data Science, or Software Engineering, with significant hands-on experience building production AI systems.

• Generative AI Expertise:

  Deep hands-on experience with

  LLMs, Generative AI, RAG, prompt engineering, embeddings, vector search, and AI agents

  .

• Technical Mastery:

  Strong proficiency in

  Python

  and experience with modern AI/ML frameworks such as

  PyTorch, Hugging Face, LangChain, LangGraph, LlamaIndex

  , or equivalent technologies.

• AI Architecture:

  Proven ability to design

  scalable, reliable AI/ML architectures

  and translate ambiguous business problems into production-ready technical solutions.

• Production Engineering:

  Strong software engineering fundamentals, including

  APIs, distributed systems, testing, CI/CD, observability, and production operations

  .

• Cloud & ML Platforms:

  Experience deploying AI/ML solutions at scale using

  AWS

  or equivalent cloud platforms, with experience in platforms such as

  Databricks, MLflow, SageMaker

  , or similar technologies.

• AI Evaluation & Quality:

  Strong understanding of

  LLM evaluation, hallucination mitigation, grounding, model quality, and AI observability

  .

• Technical Leadership:

  Demonstrated ability to influence architecture and technical direction, mentor engineers, and lead complex initiatives without necessarily having direct people-management responsibility.

Bonus Points:

• Experience building

  multi-agent / Agentic AI systems

  with orchestration, planning, memory, and tool use.
• Experience with

  document intelligence, OCR, document classification, information extraction, and multimodal AI

  .
• Experience working with

  healthcare AI, clinical workflows, medical data, RCM, billing, or claims

  .
• Familiarity with healthcare standards such as

  FHIR, HL7, X12/EDI

  , or similar healthcare data formats.
• Experience with

  HIPAA, healthcare data privacy, AI security, and responsible AI

  .
• Experience working with foundation models such as

  OpenAI, Anthropic, Llama, Mistral

  , or equivalent.
• Experience optimizing

  LLM inference cost, latency, scalability, and reliability

  .