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Boca Raton, Florida, United States
Hybrid
Not Available
Join the Team Modernizing Medicine
At ModMed, we’re not just building software—we’re reimagining the healthcare experience. Founded in 2010 by a practicing physician and a successful tech entrepreneur, we took a radically different approach: we hired doctors and taught them how to code. This "for doctors, by doctors" philosophy has allowed us to create an AI-enabled, specialty-specific cloud platform that places patients at the center of care.
A Culture of Excellence
When you join ModMed, you’re joining an award-winning team recognized for innovation and employee satisfaction. From our global headquarters in Boca Raton Florida, and extensive employee base in Hyderabad India, we are a team of 4,500+ passionate problem-solvers on a mission to increase medical practice success and improve patient outcomes:
Consistently ranked as a Top Place to Work
2025 Globee Business Awards: Gold Globee for “Technology Team of the Year”
2025 Black Book Awards: Ranked #1 EHR in 11 Specialties
Florida Venture Forum: Venture-Backed Company of the Year
We are growing fast, thinking big, and we are just getting started.
Ready to modernize medicine with us?
Job Description Summary:
As a Staff AI Engineer, you define and drive the architecture of AI and agentic systems across multiple teams and product domains. This is a senior individual-contributor leadership role: you influence high-impact architectural decisions, evolve the practices and standards for building agentic AI, and turn experimental AI capabilities into reliable production systems. You set direction for multi-agent orchestration, production RAG (hybrid search, re-ranking, and query routing), tool and MCP integration, and the evaluation and observability stack that keeps them dependable. You mentor senior engineers and represent AI engineering in cross-functional and strategic initiatives. A background in classical ML is an asset; the primary requirement is a proven track record of shipping production agentic AI.
KEY RESPONSIBILITIES
Define and drive technical direction for AI and agentic systems, and contribute to the AI platform roadmap across teams
Influence architecture decisions for compute, cloud, and AI infrastructure across teams
Lead the design of large-scale AI/LLM systems: inference platforms, APIs, and distributed architectures
Architect production multi-agent systems end-to-end: orchestration, state management, tool integration, and failure handling
Define and drive best practices and standards for AI/LLM systems across teams (agent design, evaluation, observability, reliability)
Lead complex production debugging and incident response across teams, and harden the resulting fixes into platform guardrails
Mentor senior engineers and emerging technical leaders, raising the engineering bar
Lead technical design reviews and architecture decision records (ADRs) for critical AI infrastructure
Contribute to capacity planning and cost optimization strategies for AI/LLM infrastructure
GENAI / AGENTIC AI CAPABILITIES
Define and drive vector database and RAG architecture decisions across systems and teams: structured RAG, hybrid search (dense + sparse + keyword), re-ranking, and query routing
Lead multi-agent platform architecture decisions: runtime selection, orchestration patterns, and enterprise integration strategy
Set the technical direction for MCP (Model Context Protocol) adoption and agent runtime infrastructure
Shape agent infrastructure adoption: evaluate and standardize frameworks, tooling, and deployment patterns for agentic AI
Architect evaluation infrastructure for non-deterministic LLM systems: synthetic golden-set generation, hierarchical weighted scoring (component, composite, and system-level F1), bootstrap confidence intervals, and paired A/B comparison, treating a change as real only when it is both statistically significant and clears a minimum effect size
Gate deployments on eval results: tiered regression thresholds (hard-gate vs monitor components) wired into CI so a measurable quality regression blocks the release, with observability via tracing across multi-step chains and tool calls and drift detection on LLM inputs and outputs
Drive LLM cost optimization at scale: model routing, caching, batching, token budget management, and provider cost analysis
REQUIRED SKILLS & QUALIFICATIONS
Master’s or Ph.D. degree in Computer Science, Software Engineering, or a related field.
10+ years of professional experience in ML/AI or software engineering, including 4+ years in senior or staff-level roles with production system ownership
Demonstrated engineering leadership, including driving technical strategy and influencing cross-team decisions
Expertise in platform and distributed-systems architecture at scale: model serving, APIs, data platforms, and AI/LLM infrastructure
Hands-on experience architecting and operating production agentic AI or LLM systems (multi-agent workflows, production RAG, tool and MCP integration)
Deep understanding of embedding models, retrieval algorithms, and vector database internals
Strong production debugging, reliability, and incident-response skills
Experience building rigorous evaluation for non-deterministic AI systems, including statistical methods (such as bootstrap confidence intervals and minimum effect-size thresholds) to separate genuine quality changes from run-to-run model variance
Cost-awareness for cloud AI/LLM workloads: capacity planning and cost optimization
Proven mentorship of mid-level and senior engineers
Strong communication skills for executive and cross-functional audiences
PREFERRED QUALIFICATIONS (NICE TO HAVE)
Experience in Healthcare, FinTech, or other regulated industries
Experience building AI/LLM systems or platform components from the ground up
Defined best practices for AI-assisted development (Claude Code): code quality standards, review, and responsible usage across teams
Track record of conference talks, published papers, or significant open-source contributions
Experience with GPU-accelerated inference and model serving optimization
Familiarity with workflow orchestration and streaming architectures for real-time AI
ModMed Benefits Highlight: At ModMed, we believe it’s important to offer a competitive benefits package designed to meet the diverse needs of our growing workforce. Eligible Modernizers can enroll in a wide range of benefits:
United States
PHISHING SCAM WARNING: ModMed is among several companies recently made aware of a phishing scam involving imposters posing as hiring managers recruiting via email, text and social media. The imposters are creating misleading email accounts, conducting remote "interviews," and making fake job offers in order to collect personal and financial information from unsuspecting individuals. Please be aware that no job offers will be made from ModMed without a formal interview process, and valid communications from our hiring team will come from our employees with a ModMed email address (first.lastname@modmed.com). Please check senders’ email addresses carefully. Additionally, ModMed will not ask you to purchase equipment or supplies as part of your onboarding process. If you are receiving communications as described above, please report them to the FTC website.