Staff ML Engineer
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Job Description
Staff ML Engineer scaling production AI agents for Press Ganey, a healthcare experience measurement and analytics provider. Leading enterprise AI architecture across Java/Spring platforms and distributed systems.
Responsibilities:
- Design, build, and deploy production-ready AI agents and agentic workflows integrated with enterprise applications and business processes
- Establish evaluation, monitoring, guardrail, and safety frameworks for LLM-powered applications
- Architect and implement scalable AI-enabled capabilities within the 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 to improve product capabilities and developer productivity
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, including Spring Boot and Spring Framework
- Experience building and evolving enterprise-scale applications
- Deep expertise building scalable, production-grade AI-enabled applications and distributed systems
- 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
- Extensive experience designing and deploying production-grade LLM applications using LangChain, LangGraph, Spring AI, Model Context Protocol (MCP), or similar technologies
- Strong understanding of Retrieval-Augmented Generation (RAG), tool calling, 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
- Experience with Databricks, vector search technologies, embedding models, conversational AI, and evaluation strategies for AI agents preferred
- Experience building AI infrastructure, developer tooling, and platform capabilities preferred
- Experience architecting and maintaining large-scale Java microservices using Spring Boot preferred
- Experience with AWS, Azure, or GCP, Kubernetes, and containerized deployments preferred
- Familiarity with model serving, inference optimization, caching strategies, and cost optimization for enterprise AI systems preferred
Benefits:
- Competitive benefits package
- Discretionary bonus or commission tied to achieved results
- Reasonable accommodations for qualified individuals with disabilities or disabled veterans in the hiring process
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