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Data & AI Engineer (LLMs & Distribution Analytics)
Job Location:
Job Location:
Boston, MA - USA
Yearly Salary:
USD 100000 - 130000
Yearly Salary:
Posted:
21 October 2026 (Yesterday)
Posted:
Application Deadline:
18 January 2027
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Job Role: Data & AI Engineer (LLMs & Distribution Analytics)
Job Location: Boston MA (Day 1 Onsite)
Job Type: Full Time
Salary Range: $100000 to $130000/Annum Full Time Benefits
Job Description
Join a high-impact Data & AI engineering team at the forefront of enterprise AI transformation. Youll build production-grade AI solutions (LLMs RAG and agent workflows) used directly by Sales Marketing and Distribution teams across EMEA.
This is a hands-on engineering role where you will work with modern cloud-native data platforms and AI tooling to turn commercial data into actionable intelligence. You will contribute to a growing AI agenda with direct exposure to senior leadership and real business impact.
Roles & Responsibilities
Work on enterprise-scale AI initiatives with visible business impact
Build real-world generative AI solutions (not just prototypes)
Access cutting-edge technologies including AWS Bedrock and Snowflake Cortex
Partner with global teams across engineering data science and business domains
Opportunity to shape and scale AI capabilities in a leading asset management firm
Clear progression into senior AI/data engineering roles
What Success Looks Like (First 12 Months)
Deliver production-ready AI use cases (e.g. AI agents for sales and distribution insights)
Integrate key CRM and marketing datasets into a unified analytics platform
Improve reliability and scalability of commercial data pipelines
Contribute to enterprise AI adEligible to workion through working solutions and PoCs
Establish strong engineering practices in data and AI delivery
What Youll Do
Build AI & Advanced Analytics Solutions
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 productions AI capabilities
Develop Cloud Data Pipelines
Build and maintain scalable data pipelines across ingestion transformation and serving layers
Work with AWS services (S3 Glue Lambda Athena) and Snowflake/Redshift
Write production-grade code in Python and/or PySpark
Integrate Commercial & CRM Data
Design and implement integrations for Salesforce CRM Marketing Cloud and web analytics platforms
Work at API and schema level to connect multiple data sources
Identify and resolve data quality issues across pipelines and source systems
Drive Engineering Quality
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
Prototype & Innovate
Lead proof-of-concept work for new AI and data capabilities
Evaluate emerging tools and frameworks and recommend adEligible to workion
Translate experimentation into practical solutions for the platform roadmap
Tech Stack
Cloud: AWS (S3 Glue Lambda Athena)
Data Platforms: Snowflake Redshift
Languages: Python PySpark
AI/ML: AWS Bedrock Snowflake Cortex
AI Patterns: LLMs RAG vector databases agent frameworks
CRM & Data Sources: Salesforce Marketing Cloud third-party commercial data
Visualization (Eligible to workional): Tableau or equivalent
Essential Skills
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 in integrating Salesforce CRM data and commercial data sources
Understanding of data pipelines across ingestion transformation and serving
Ability to work Consultantly with strong delivery discipline and ownership.
Nice to Have
Experience with MLOps feature engineering or model serving
Exposure to multi-agent frameworks (e.g. LangGraph CrewAI AWS Agent Core)
Experience of onboarding third-party commercial datasets (e.g. fund flows market intelligence)
Experience with BI tools (Tableau or similar) for business-facing analytics
Experience & Education
4 years of experience in data engineering analytics platforms or software development
Proven track record of hands-on delivery in cloud-native environments
Job Location: Boston MA (Day 1 Onsite)
Job Type: Full Time
Salary Range: $100000 to $130000/Annum Full Time Benefits
Job Description
Join a high-impact Data & AI engineering team at the forefront of enterprise AI transformation. Youll build production-grade AI solutions (LLMs RAG and agent workflows) used directly by Sales Marketing and Distribution teams across EMEA.
This is a hands-on engineering role where you will work with modern cloud-native data platforms and AI tooling to turn commercial data into actionable intelligence. You will contribute to a growing AI agenda with direct exposure to senior leadership and real business impact.
Roles & Responsibilities
Work on enterprise-scale AI initiatives with visible business impact
Build real-world generative AI solutions (not just prototypes)
Access cutting-edge technologies including AWS Bedrock and Snowflake Cortex
Partner with global teams across engineering data science and business domains
Opportunity to shape and scale AI capabilities in a leading asset management firm
Clear progression into senior AI/data engineering roles
What Success Looks Like (First 12 Months)
Deliver production-ready AI use cases (e.g. AI agents for sales and distribution insights)
Integrate key CRM and marketing datasets into a unified analytics platform
Improve reliability and scalability of commercial data pipelines
Contribute to enterprise AI adEligible to workion through working solutions and PoCs
Establish strong engineering practices in data and AI delivery
What Youll Do
Build AI & Advanced Analytics Solutions
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 productions AI capabilities
Develop Cloud Data Pipelines
Build and maintain scalable data pipelines across ingestion transformation and serving layers
Work with AWS services (S3 Glue Lambda Athena) and Snowflake/Redshift
Write production-grade code in Python and/or PySpark
Integrate Commercial & CRM Data
Design and implement integrations for Salesforce CRM Marketing Cloud and web analytics platforms
Work at API and schema level to connect multiple data sources
Identify and resolve data quality issues across pipelines and source systems
Drive Engineering Quality
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
Prototype & Innovate
Lead proof-of-concept work for new AI and data capabilities
Evaluate emerging tools and frameworks and recommend adEligible to workion
Translate experimentation into practical solutions for the platform roadmap
Tech Stack
Cloud: AWS (S3 Glue Lambda Athena)
Data Platforms: Snowflake Redshift
Languages: Python PySpark
AI/ML: AWS Bedrock Snowflake Cortex
AI Patterns: LLMs RAG vector databases agent frameworks
CRM & Data Sources: Salesforce Marketing Cloud third-party commercial data
Visualization (Eligible to workional): Tableau or equivalent
Essential Skills
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 in integrating Salesforce CRM data and commercial data sources
Understanding of data pipelines across ingestion transformation and serving
Ability to work Consultantly with strong delivery discipline and ownership.
Nice to Have
Experience with MLOps feature engineering or model serving
Exposure to multi-agent frameworks (e.g. LangGraph CrewAI AWS Agent Core)
Experience of onboarding third-party commercial datasets (e.g. fund flows market intelligence)
Experience with BI tools (Tableau or similar) for business-facing analytics
Experience & Education
4 years of experience in data engineering analytics platforms or software development
Proven track record of hands-on delivery in cloud-native environments
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