Role: Engineer
Required Skills: Artificial Intelligence
Experience: 6 - 10 Years
Function: TECHNOLOGY
Apply By: 2026-12-15
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
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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
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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
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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
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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
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