Job description

Data & AI Engineer (LLMs & Distribution Analytics) Join a high-impact Data & AI engineering team at the forefront of enterprise AI transformation. You’ll 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 adoption through working solutions and PoCs • Establish strong engineering practices in data and AI delivery ________________________________________ 🔹 What You’ll 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 • Contr ibute 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 adoption • 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 (Optional): Tableau or equivalent ________________________________________ 🔹 What You Must Bring (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 independently 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 • 4–7 years of experience in data engineering, analytics platforms, or software development • Proven track record of hands-on delivery in cloud-native environments Salary Range- $100,000-$120,000 a year #LI-SP3 #LI-VX1 </div

Requirements

Must-haves

Data & AI Engineer (LLMs & Distribution Analytics)
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 adoption through working solutions and PoCs
Establish strong engineering practices in data and AI delivery
________________________________________
What You’ll Do
Build AI & Advanced Analytics Solutions

Nice-to-haves

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
Proven track record of hands-on delivery in cloud-native environments

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiawsmlpythonapillm

Platform: careers-page
Effort: medium