Data & AI Engineer (LLMs & Distribution Analytics)

Job DescriptionJob DescriptionJob 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. 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 ________________________________________ =9 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 ________________________________________ =9 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 " 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 ________________________________________ =9 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 ________________________________________ =9 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. =9 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 =9 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