AWS Amazon Connect Agentic AI Engineer

The Motley Fool is a purpose-driven financial services company on a mission to make the world smarter, happier, and richer. For 30 years, we’ve been helping people make better investment decisions through transparency, education, and a healthy dose of Foolish fun. We’re a fast-moving, collaborative team that values high-quality work, curiosity, and initiative. We care deeply about what we do, and we’re driven by the impact our work has on real people’s financial futures.

Our Internal Tech team builds out tools and tech to help Fools do their best work. In this case, we’re looking to evolve our systems to keep our members supported, connected, and heard. We currently run an active Amazon Connect-based voice contact center integrated with HubSpot to manage member communications. Rather than building a greenfield environment, our focus is to extend and modernize this system by layering in next-generation AI agent capabilities, Amazon Q in Connect, and native AWS integrations to resolve customer interactions seamlessly.

The AWS Amazon Connect Agentic AI Engineer will play a critical role in shaping the future of our customer experience. In this hands-on contract role, you will deliver a phased roadmap for AI-driven member service workflows. You will design and deploy practical, automated agentic features.

Success looks like members getting fast, accurate answers and resolution to their needs without waiting, with the AI handling the full range of common interactions end-to-end. When complex situations do require additional support, the AI provides full context so the experience remains seamless. The result is a well-documented, IaC-managed foundation that supports the next phases of our roadmap.

• 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.

• Are a pragmatic, hands-on AI builder who prioritizes stable, production-grade solutions over theoretical hype.
• Take pride in writing exceptionally clear technical documentation and operational runbooks for long-term reliability.
• Think deeply about continuous customer contexts, ensuring experiences translate fluidly across voice, email, and live chats.
• Approach engineering with a consultant's mindset, helping us analyze strategic choices like when to consolidate support channels.
• Bring sound engineering judgment when introducing autonomous agents to highly sensitive financial and personal account workflows.

• Strong production experience designing, building, and deploying Amazon Connect contact flows, queues, and routing profiles.
• Hands-on experience working with Amazon Connect generative AI capabilities, including Amazon Q in Connect, post-contact summaries, and prompt guardrails.
• Expert-level Python skills, particularly for AWS Lambda integrations and backend microservices.
• Deep implementation experience across the AWS ecosystem, specifically Lex, Bedrock, DynamoDB, S3, Kinesis, CloudWatch, and IAM.
• Strong working knowledge of Amazon Connect’s current agentic AI stack, including agentic self-service, Bedrock Knowledge Bases, and MCP.
• Proven experience managing Amazon Connect deployments via Infrastructure as Code using CloudFormation, CDK, or Terraform.
• Experience integrating contact center systems with enterprise CRMs (HubSpot preferred) and third-party SaaS APIs.
• Experience designing voice and email as a unified conversation thread, designing custom session context models, or tuning prompts based on production sentiment analysis (preferred).
• Experience with post-contact summaries, transfer summaries, or agent-assist capabilities (preferred).