Data & AI Engineer - (Hybrid)

Responsibilities

• Design and operate data pipelines on AWS — Glue, Step Functions, Lambda, EventBridge, S3 — feeding the Redshift data warehouse.
• Stand up and operate containerized production pipelines on AWS Fargate / ECS (scheduled ingest or scrape, enrich, deliver) with CloudWatch alarms and health monitoring.
• Create dimensional data models — facts, conformed dimensions, and analytics marts — on Redshift over a zero-ETL replica of the operational source.
• Implement document-extraction pipelines using Amazon Bedrock Data Automation blueprints and deliver structured output to downstream consumers via webhook or queue.
• Build and operate Bedrock Knowledge Bases for retrieval-augmented generation: source preparation, indexing, retrieval evaluation, and cost / latency tuning.
• Build agents using the Strands Agents SDK on Bedrock AgentCore — supervisor / sub-agent topologies, tool definitions, and deployment hardening.
• Develop applied-LLM data products for reporting, search, and agentic operations.
• Deploy and operate services on AWS end to end, including internal web apps and demos.
• Build internal tooling and integrations, including MCP servers.
• Prototype and ship new AI-powered applications for advisors and internal teams.
• Maintain operational quality — logs, alarms, runbooks, on-call response, post-incident notes — and continuously monitor quality and compliance with data-privacy regulations.

Requirements

• Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, or a related field. Master's preferred at the Senior level.
• Relevant production experience scaled to level (Data & AI Engineer I / II / Senior).
• Authorization to work in the United States without sponsorship.

Competencies

• Technical (builds with) AWS data and serverless services.
• Amazon Bedrock and AgentCore Runtime.
• Python (primary); SQL (baseline).
• Data warehousing and dimensional modeling.
• Agent and LLM frameworks.
• Infrastructure-as-code.

Tooling

• Claude Code as the primary development surface, including parallel sessions.
• MCP servers (AWS, Excolo, Atlassian) as deterministic tool routing for work that previously spanned terminal, IDE, and browser.

Operational

• Writes documentation a teammate can pick up and act on without a meeting.
• Explains trade-offs in plain language to non-engineers (Marketing, Operations, Finance).
• Strong problem-solving, communication, and collaboration skills.