Applied AI Engineer - (ML / AI / AGI)

Position Summary 


The 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. 

Key Responsibilities:

•    Design and implement AI solutions for ranking, summarization, extraction, classification, recommendation, and conversational workflows. 
•    Develop prompt-based and model-based solutions using Python and modern AI orchestration patterns. 
•    Work with structured and unstructured data stored or processed in S3, Redshift, Athena, Glue, EMR, and Databricks. 
•    Build evaluation, testing, and monitoring approaches for AI-enabled workflows and agentic systems. 
•    Partner with business, engineering, and governance stakeholders to translate operational pain points into production AI features. 
•    Support reusable prompt libraries, agent patterns, and service interfaces for internal AI products. 
•    Contribute to responsible AI practices including grounding, escalation paths, review controls, and measurable success criteria. 

Qualifications:

•    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. 

Preferred Qualifications:

•    Experience with enterprise search, retrieval, recommendation systems, or document intelligence workflows. 
•    Exposure to responsible AI controls, policy constraints, or model risk/compliance frameworks. 
•    Experience in insurance, financial services, HR tech, staffing, or workflow automation is a plus. 

 
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