Applied AI Engineer

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.

• 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.