Sr. Analyst, Applied AI Engineer

The Role at a Glance

The Sr. Applied AI Engineer designs and builds intelligent services and agentic workflows that sit on top of the cloud, data, and application stack. This role creates production-ready solutions for ranking, summarization, retrieval, classification, recommendation, and decision support using Python and governed enterprise AI development practices. 

What you'll be doing

• Leads the design and implementation of AI solutions for ranking, summarization, extraction, classification, recommendation, and conversational workflows across complex or multi-stakeholder use cases.
• Develops prompt-based and model-based solutions using Python and modern AI orchestration patterns, independently evaluating technical options and recommending scalable approaches.
• Works across structured and unstructured data in cloud and enterprise data environments to design reliable, governed AI workflows that integrate with broader data and application ecosystems.
• Establishes and enhances evaluation, testing, and monitoring approaches for AI-enabled workflows and agentic systems to improve accuracy, quality, reliability, and operational readiness.
• Partners with business, engineering, product, and governance stakeholders to translate ambiguous operational pain points into production AI features, success measures, and implementation plans.
• Advances reusable prompt libraries, agent patterns, and service interfaces for internal AI products, promoting consistency, scalability, and adoption across teams.
• Applies and helps strengthen responsible AI practices, including grounding, escalation paths, review controls, policy constraints, and measurable success criteria for AI-enabled solutions.
• Provides technical guidance to peers and project teams by sharing best practices, reviewing solution approaches, and influencing adoption of effective AI engineering patterns. 

What we’re looking for

•    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, that directly aligns with the specific responsibilities for this position. 5+ years of experience in ML engineering, applied AI, NLP, LLM engineering, or a related field. 
•    Strong Python experience. 
•    Experience productionizing AI or ML workflows on AWS or similar cloud platforms. 
•    Familiarity with Databricks, MLflow, model evaluation, and governed data environments. 
•    Experience working with SQL and distributed processing tools such as PySpark. 
•    Experience with SageMaker Studio, AgentCore are plus 
•    Strong communication and product collaboration skills. 

Application Deadline