Distribution & Analytics GenAI Engineer

Ameriprise Financial Services, LLC

. Design and develop AI workflows using LLMs, RAG, and agent-based frameworks .

Posted 10/22/2026full-timeBoston • Massachusetts • United StatesMid-LevelSenior💰 $123,100 - $169,200 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and developing AI workflows using LLMs and cloud-native data engineering solutions. Proficient in building scalable data pipelines and integrating various data sources while ensuring data quality and reliability.

Highest-signal resume keywords

AI Workflow DevelopmentCloud Data EngineeringPython ProgrammingSalesforce CRM IntegrationData Pipeline Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI WorkflowsData EngineeringMachine Learning PipelinesPythonPySparkData Quality ManagementFeature EngineeringMLOpsAPI IntegrationTechnical Design

Soft Skills

Independent WorkDelivery DisciplineCollaborationProblem SolvingOwnership

Tools & Technologies

AWS BedrockSnowflakeAWS S3AWS GlueAWS LambdaAWS AthenaRedshiftSalesforce Marketing CloudTableauLangGraph

Certifications & Qualifications

Bachelor’s Degree in Computer ScienceEngineering Degree

Industry Keywords

Cloud-Native EnvironmentsAI SolutionsData PipelinesCommercial Data SourcesBI Tools

Tech Stack

Tools & technologies

Amazon RedshiftAWSCloudPySparkPythonTableau

About the role

Key responsibilities & impact

Design and develop AI workflows using LLMs, RAG, and agent-based frameworks
Implement solutions using AWS Bedrock, Snowflake Cortex, and related services
Build ML feature pipelines and support AI use case deployment
Collaborate with data science teams to productionise AI capabilities
Build and maintain scalable data pipelines across ingestion, transformation, and serving layers
Work with AWS services including S3, Glue, Lambda, and Athena, as well as Snowflake and Redshift
Write production-grade code in Python and/or PySpark
Design and implement integrations for Salesforce CRM, Marketing Cloud, and web analytics platforms
Connect multiple data sources at API and schema level
Identify and resolve data quality issues across pipelines and source systems
Contribute to code reviews, testing practices, and pipeline reliability improvements
Participate in technical design discussions and architecture reviews
Identify and address technical debt to improve platform performance
Lead proof-of-concept work for new AI and data capabilities
Evaluate emerging tools and frameworks and recommend adoption
Translate experimentation into practical solutions for the platform roadmap
Deliver production-grade AI solutions used by Sales, Marketing, and Distribution teams across EMEA

Requirements

What you’ll need

4–7 years of experience in data engineering, analytics platforms, or software development
Proven track record of hands-on delivery in cloud-native environments
Bachelor’s degree in computer science, Engineering, or equivalent experience
Strong hands-on experience in cloud data engineering (AWS + Snowflake/Redshift)
Proven experience building AI/LLM-based solutions using orchestration frameworks and managed services
Solid programming skills in Python and/or PySpark
Experience integrating Salesforce CRM data and commercial data sources
Understanding of data pipelines across ingestion, transformation, and serving
Ability to work independently with strong delivery discipline and ownership
Valid work authorization that does not now, or in the future, require visa sponsorship for employment in the United States
Preferred: experience with MLOps, feature engineering, or model serving
Preferred: exposure to multi-agent frameworks such as LangGraph, CrewAI, or AWS Agent Core
Preferred: experience onboarding third-party commercial datasets
Preferred: experience with BI tools such as Tableau or similar

Benefits

Comp & perks

Variable pay in the form of bonus, commissions, and/or long-term incentives, depending on the role
Vacation time
Sick time
401(k)
Health insurance
Dental insurance
Life insurance
Flexible work arrangement: work from home one (1) day per week
Reasonable accommodations during recruitment and interviews for individuals with disabilities