AWS Connect Implementation Expert – Amazon Connect CCaaS Platform Engineering

AWS Connect Implementation Expert – Amazon Connect CCaaS Platform Engineering We're building customer-facing contact-center solutions on Amazon Connect and we're looking for an implementation expert with deep, hands-on experience standing up, integrating, and operating production Connect instances. We are a service-as-a-software company — our engineering team works closely with and for our ops teams to build the best service-as-a-software product possible. The contact flows, routing, and integrations you build handle real customer traffic and plug into real operational workflows, so reliability, call quality, and clean escalation all matter. This is not a generic AWS or backend role. We need someone who has actually designed, deployed, and run Amazon Connect (CCaaS) in production — and who understands the full stack from inbound call to agent desktop to reporting. BEFORE YOU APPLY We work exclusively with independent developers. Any agency that applies will be automatically rejected. We will ask to see real examples of Amazon Connect implementations you've built and shipped — ideally with walkthroughs of contact flows, integrations, and architecture. Please have those ready before reaching out. WHAT YOU MUST KNOW Amazon Connect Core Standing up and configuring Amazon Connect instances end-to-end — from claiming numbers to a live, routed contact center Designing contact flows / flow modules for voice and chat — prompts, branching, error handling, and reusable modules Routing — queues, routing profiles, hours of operation, quick connects, priority/agent proficiency-based routing Telephony — claiming and porting numbers, DIDs/toll-free, DTMF, call recording, and audio quality Lambda integration from within flows — invoking functions for lookups, decisions, and system-of-record reads/writes Amazon Lex bots for self-service, intent handling, and IVR replacement, wired into Connect flows Contact attributes — capturing, passing, and persisting context across the contact lifecycle Strong TypeScript and/or Python for the Lambda / integration layer INTEGRATION, CTI & THE AGENT EXPERIENCE A big part of our work is connecting Connect into surrounding systems and giving agents the right desktop, so experience here stands out. Amazon Connect Streams / Agent Workspace / CTI — embedding the CCP, building custom agent desktops, and screen-pops CRM & system-of-record integrations — Salesforce, ServiceNow, Zendesk, or similar Warm transfers, escalation to human agents, callbacks, and skills-based routing Carrying context across the contact lifecycle and handing off cleanly to live agents Outbound — Connect outbound / high-volume outbound, campaigns, and API-initiated calls DATA, REPORTING & OPERATIONS Contact Lens — real-time and post-contact analytics, sentiment, and categorization Kinesis streams (contact trace records, agent events) and downstream analytics/data lakes Real-time and historical metrics, custom dashboards, and reporting for ops teams Infrastructure-as-code for Connect (CloudFormation / CDK / Terraform), IAM, and multi-environment setups Monitoring, alarming (CloudWatch), and designing for failure modes and graceful fallback DOMAIN EXPERIENCE WE CARE ABOUT We work specifically in back-office automation, concierge, and customer support scenarios. Experience implementing Connect for any of these is a strong plus. You should understand the nuances of these environments — things like: Escalation flows and warm transfers to human agents Structured data collection mid-contact (and writing it back to a system of record) Blending self-service (bot/IVR) with live-agent handling seamlessly Designing for failure modes — misrecognition, silence, dropped calls, and clean fallback Meeting compliance and recording requirements where they apply HOW WE WORK Direction, principles, and implementation conventions are heavily shaped by our pre-built set of gen-AI plugins, skills, and commands. They're there to support you, not box you in. Much of how things get done is already encoded in our internal tooling, so you spend less time on boilerplate and setup and more on building The conventions give you a strong, opinionated foundation to move fast and stay consistent with the rest of the team Part of the job is leaning on these tools, then helping improve and extend them as you go AI-POWERED DEVELOPMENT We are an AI-first team and expect every developer we work with to operate the same way. Proficiency with generative AI coding tools is not a nice-to-have — it is a hard requirement. Specifically, we require fluency with agentic coding tools like Claude Code and Codex, including: Best practices around context management Prompt engineering for development tasks Using MCPs (Model Context Protocol servers) to extend and accelerate workflows You should be using these tools daily to speed up development, assist with code review, scaffold features, and maintain quality. Developers who are not actively working this way will not be a good fit for this role. If this sounds like a fit, tell us about yourself, the Amazon Connect implementations you've shipped, and drop any relevant links, architecture walkthroughs, or demos.