The Motley Fool

Data Engineer

• Design, build, and take full ownership of the data infrastructure powering our investment operations.
• Own the complete data lifecycle, spanning ingestion, transformation, warehousing, analytics, and machine learning.
• Architect ETL/ELT pipelines orchestrated by Apache Airflow (AWS MWAA).
• Build and tune a Snowflake data warehouse fed by S3 data lakes.
• Develop analytical models and dashboards that turn raw data into actionable intelligence.
• Lead the transformation of our data infrastructure from manual processes to scalable, governed, automated data systems.
• Replace manual file drops with event-driven Airflow DAGs and AWS Lambda functions.
• Define all cloud infrastructure with Terraform or AWS CDK.
• Establish clean, governed, and accessible datasets that feed AI agents and intelligent automation.

Senior Data Engineer

Full-stack Engineer

• Build and maintain server-side features in our Next.js App Router codebase using TypeScript — route handlers, server components, server actions, streaming, ISR, and revalidation strategy.
• Design and harden integrations with the third-party APIs that power our content, market data, and subscription experiences. We care a lot about doing this well: timeouts, retries, circuit breakers, fallbacks, and graceful degradation when upstream services misbehave are first-class concerns, not afterthoughts.
• Own caching strategy across Redis and Cloudflare, balancing freshness against performance, cost, and crawler behavior.
• Deploy and operate services on AWS using Docker, with first-class instrumentation in DataDog so we catch issues before our readers and crawlers do.
• Write meaningful end-to-end coverage with Microsoft Playwright for the flows that matter most.
• Optimize the site for the way it's actually consumed by SEO crawlers: rendering strategy, structured data, sitemap generation, canonicalization, hreflang, robots directives, performance budgets, and crawl budget management.
• Partner with our front-end engineers on the seam between server and client, and collaborate with content, marketing, SEO, and platform teams across the company.
• Use AI-assisted development tools (Claude Code, Cursor) as a core part of your daily workflow — we have a company-wide commitment to use the latest tooling and workflows to make every person as impactful as possible.
• Integrate with our CMS for content management

Senior Software Engineer, Next.JS

Backend Engineer

• Develop new features for our core commerce and customer engagement platforms.
• Work directly with stakeholders to iterate and get rapid feedback on feature development.
• Appropriately use AI tools like Claude Code and multi-agent workflows on a daily basis to assist with planning and implementation.
• Ensure our critical transactional and event systems have high availability, durability, accuracy (since money is on the line), and remain highly performant.
• Build and enhance admin tooling and workflows that enable our internal business stakeholders to be more self-sufficient.
• Ensure features meet acceptance criteria and are supported by robust automated test coverage.
• Integrate with third-party providers and tools (such as Stripe and Braze)—leveraging their existing functionality and working around their limitations.
• Investigate, troubleshoot, and fix reported bugs and Sentry errors.
• Collaborate with the Product Owner and Project Manager to break down business requirements into clear technical stories and tasks.
• Partner with multiple in-house engineering squads and external providers to launch customer-facing solutions.
• Review peer code and participate in our team’s on-call rotation to maintain system reliability.
• Support and scale platforms across multiple countries.

Senior Python Developer

AI Engineer

• Deliver phase-one AI capabilities in our existing Amazon Connect environment, focusing on AI-first call handling, intelligent routing, and autonomous resolution of common login, account, and password-reset queries.
• Design AI-first workflows for voice and email that prioritize autonomous resolution, allowing the system to intelligently decide when to handle a request end-to-end and when to route to an agent.
• Leverage our existing call recordings and transcripts to extract real interaction patterns and customer language to ground the AI in actual member needs.
• Build elegant handoff patterns that preserve a member's interaction history, intent, and attempted actions so they never have to repeat themselves.
• Write clean, production-ready Python backend code and AWS Lambda integrations to handle secure account lookups, validation, and CRM updates.
• Integrate Amazon Connect workflows with HubSpot and other internal systems to equip the AI agent with real-time customer context.
• Establish a reusable metadata and session strategy to enrich ongoing and future interactions with purchase history and communication logs.
• Tune RAG (Retrieval-Augmented Generation) patterns and Bedrock Knowledge Bases to keep AI responses grounded in approved policies and procedures.
• Implement practical guardrails that keep AI responses focused on approved topics and apply secure verification steps for sensitive workflows.
• Deploy and manage AWS resources using CloudFormation, CDK, or Terraform, ensuring version-controlled deployments of Connect flow JSONs.
• Author clean, clear architecture runbooks, deployment procedures, and prompt configurations to ensure the wider team can easily operate your work.
• Lay the technical foundations for future authenticated transactions like billing updates, self-service cancellations, and payment processing.

AWS Amazon Connect, AI Engineer

Marketing

• Own day-to-day Always On marketing across site ads, order pages, automated campaigns, and targeted member experiences.
• Identify high-impact growth opportunities through experimentation, segmentation, behavioral analysis, and lifecycle performance insights.
• Design and scale experimentation frameworks across lifecycle touchpoints, messaging, offers, timing, targeting, and channel strategy.
• Build scalable lifecycle systems, workflows, and operational processes that improve efficiency and marketing performance over time.
• Influence lifecycle strategy and prioritization across Product, Marketing, Analytics, and Engineering stakeholders.
• Leverage AI and automation to improve targeting, accelerate analysis, scale testing, optimize creative iteration, and enhance operational decision-making.
• Write, refine, or adapt direct-response messaging and marketing copy using AI-assisted workflows and performance insights.
• Translate complex data and experimentation results into actionable business recommendations and growth opportunities.
• Help evolve segmentation strategy, lifecycle architecture, and personalization capabilities across the member journey.
• Work closely with lifecycle systems, experimentation tools, analytics environments, and machine learning-supported marketing platforms.
• Balance strategic leadership with hands-on execution and rapid iteration.

Senior Data Engineer

Senior Software Engineer, Next.JS

Senior Python Developer

AWS Amazon Connect, AI Engineer

Senior Lifecycle Marketing Manager