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Applied AI Engineer - (ML / AI / AGI)
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- Posted 30 days ago
- Be among the first 10 applicants
Job Description
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.
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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