work with user groups to solve business problems with agentic AI.
build a world class agentic AI enterprise capability leveraging cloud platforms, analytics, and agile development methodologies.
meet with industry experts, reviewing/selecting enterprise technology tools and processes, designing solutions, and getting hands on with the implementation.
Requirements
Proven experience working with ML engineering teams and delivering ML-powered systems in production at scale.
Understanding of generative AI systems, including hands-on experience working with large language models (LLMs), embeddings, retrieval pipelines, prompt engineering, and evaluation strategies.
Strong engineering fundamentals: modern software development practices, cloud-native architectures (preferably in Azure), and ML lifecycle tools.
Experience designing AI capabilities or shared services used by multiple product teams.
Familiarity with tools like LangChain, LangGraph, LlamaIndex, OpenAI APIs, HuggingFace, Weaviate/FAISS, and vector databases.
Experience in regulated industries like healthcare, insurance, or finance.
Prior experience standing up developer platforms or internal ML tooling.
Excellent communication and collaboration skills—you can translate between technical and business stakeholders and rally others around a shared vision.
Benefits
medical, dental and vision benefits
401(k) retirement savings plan
time off (including paid time off, company and personal holidays, volunteer time off, paid parental and caregiver leave)
short-term and long-term disability
life insurance
many other opportunities
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learning engineeringgenerative AI systemslarge language modelsembeddingsretrieval pipelinesprompt engineeringevaluation strategiescloud-native architecturesML lifecycle toolsAI capability design
Soft skills
communication skillscollaboration skillsstakeholder managementvision alignment