Staff ML Engineer

Press Ganey

2d•$130,000 - $190,000

About The Position

Press Ganey is seeking a Staff ML Engineer to transition AI Agent prototypes into scalable, supported products. This role involves leading major AI initiatives across business units, defining engineering standards for production AI systems, and guiding the technical direction of AI Agents for Healthcare. The Staff ML Engineer will collaborate with AI Scientists, ML Engineers, Product Managers, and Software Engineers to deliver advanced AI Agents. This position will work within an existing Java and Spring-based platform, enhancing it with AI capabilities while ensuring scalability, observability, security, and maintainability.

Requirements

Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
8+ years of professional software engineering experience, including leading complex technical initiatives in distributed systems.
Strong proficiency in Python, Java and the Spring ecosystem (Spring Boot, Spring Framework), with experience building and evolving enterprise-scale applications.
Deep expertise building scalable, production-grade AI-enabled applications and distributed systems.
Demonstrated experience architecting and deploying AI agents, agentic workflows, and LLM-powered applications at enterprise scale.
Hands-on experience integrating AI capabilities into existing enterprise applications rather than building standalone AI prototypes.
Extensive experience designing and deploying production-grade LLM applications using frameworks such as LangChain, LangGraph, Spring AI, Model Context Protocol (MCP), or similar technologies.
Strong understanding of Retrieval-Augmented Generation (RAG), tool calling, Model Context Protocol (MCP), prompt engineering, and agent orchestration.
Expertise in observability, CI/CD, automated testing, and production operations for AI applications.
Proven ability to navigate ambiguity, reduce technical risk, and influence architectural direction across cross-functional teams.
Excellent communication, collaboration, and mentoring skills.

Nice To Haves

Experience with Databricks, vector search technologies, embedding models, conversational AI, and evaluation strategies for AI agents.
Experience building AI infrastructure, developer tooling, and platform capabilities that enable teams to rapidly deliver AI-powered features.
Experience architecting and maintaining large-scale Java microservices using Spring Boot.
Experience with cloud-native platforms (AWS, Azure, or GCP), Kubernetes, and containerized deployments.
Familiarity with model serving, inference optimization, caching strategies, and cost optimization for enterprise AI systems.

Responsibilities

Design, build, and deploy production-ready AI agents and agentic workflows that integrate seamlessly with enterprise applications and business processes.
De-risk complex AI integrations by establishing robust evaluation, monitoring, guardrail, and safety frameworks for LLM-powered applications.
Architect and implement scalable AI-enabled capabilities within our existing Java/Spring platform and distributed microservices ecosystem.
Establish engineering best practices for AI Agent systems, including observability, testing, deployment, versioning, and operational excellence.
Drive architectural decisions across AI services, microservices, APIs, and enterprise application integrations.
Collaborate with AI Scientists and ML Engineers to productionize models and translate experimentation into reliable software.
Mentor engineers, lead architectural reviews, and influence technical strategy across teams.
Evaluate emerging AI technologies and recommend pragmatic adoption strategies that improve product capabilities and developer productivity.