Lead Applied AI Engineer

Overview As Sr. Applied AI Engineer, you design production-ready AI services that sit atop cloud and data stacks to power ranking, summarization, classification, and decision-support workflows. You’ll develop prompt-based and model-based solutions in Python, working with enterprise data and governance practices. You collaborate with cross-functional teams to translate pain points into scalable AI features and foster reusable patterns. This role offers impact across multi-stakeholder use cases and a path to advanced AI engineering within a mission-driven company. Compensation / BenefitsPTO/parental leave Competitive 401K and employee benefits Free financial counseling, health coaching and employee assistance program Tuition assistance program Leadership development and virtual training opportunities Work arrangements that work for you Responsibilities Design and implement AI solutions for ranking, summarization, extraction, classification, recommendation, and conversational workflows across complex use cases Develop prompt-based and model-based solutions using Python and modern AI orchestration patterns with scalable approaches Design reliable, governed AI workflows integrating with cloud and enterprise data environments Establish evaluation, testing, and monitoring for AI-enabled workflows to improve accuracy and reliability Collaborate with business, engineering, product, and governance stakeholders to translate operational pain points into production AI features and success metrics Advance reusable prompt libraries, agent patterns, and service interfaces to promote consistency and adoption across teams Promote and strengthen responsible AI practices including grounding, escalation paths, review controls, policy constraints, and measurable success criteria Provide technical guidance to peers by sharing best practices and influencing AI engineering adoption Key requirements 4 Year/Bachelor's degree or equivalent work experience (4 years of experience in lieu of Bachelor's)5–7+ years of experience in ML engineering, applied AI, NLP, LLM engineering or related field Strong Python experience Experience productionizing AI/ML workflows on AWS or similar cloud platforms Familiarity with Databricks, MLflow, model evaluation, and governed data environments Experience with SQL and distributed processing tools such as PySpark Experience with Sage Maker Studio, Agent Core is a plus Strong communication and product collaboration skillsstrong communicationproduct collaborationcross-functional teamwork PythonAWS or cloud platforms Databricks