Distribution & Analytics GenAI Forward Deployed Engineer
About The Position
Join a high-impact Data & AI engineering team supporting Columbia Threadneedle’s enterprise AI transformation. This hands-on engineering role builds production-grade AI solutions—including LLMs, RAG, and agent workflows—for Sales, Marketing, and Distribution teams across EMEA. You will use cloud-native data platforms and AI tools to turn commercial data into actionable intelligence, contribute to a growing AI agenda, and engage with senior leadership. The role focuses on developing AI and advanced analytics solutions, building scalable cloud data pipelines, integrating commercial and CRM data, improving engineering quality, and prototyping new capabilities. The position is suited to a mid-to-senior engineer who can work independently and deliver high-quality solutions but is not yet in a full architectural leadership position. The team’s technologies include AWS services such as S3, Glue, Lambda, and Athena; Snowflake and Redshift; Python and PySpark; AWS Bedrock and Snowflake Cortex; LLMs, RAG, vector databases, and agent frameworks; Salesforce, Marketing Cloud, and third-party commercial data. Tableau or equivalent visualization tools are optional. Employees work in the office at least four days per week, with flexibility to work from home one day per week. Some roles may have different or additional in-office requirements, which will be discussed during hiring. Applicants must have valid U.S. work authorization that does not now or in the future require visa sponsorship.
Requirements
- 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 using AWS and Snowflake and/or 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 U.S. visa sponsorship.
Nice To Haves
- Experience with MLOps, feature engineering, or model serving.
- Exposure to multi-agent frameworks such as LangGraph, CrewAI, or AWS Agent Core.
- Experience onboarding third-party commercial datasets, such as fund flows or market intelligence.
- Experience with BI tools such as Tableau or similar for business-facing analytics.
- Experience with Tableau or equivalent visualization tools.
Responsibilities
- 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 deployment of AI use cases.
- Collaborate with data science teams to productionize AI capabilities.
- Build and maintain scalable data pipelines across ingestion, transformation, and serving layers.
- Use AWS services such as S3, Glue, Lambda, and Athena, and work with 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 the 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.
Benefits
- Vacation time
- Sick time
- 401(k)
- Health insurance
- Dental insurance
- Life insurance
- Variable pay may be available in the form of bonus, commissions, and/or long-term incentives, depending on the role.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
