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Caylent

AWS-focused cloud-native consulting and DevOps

Senior CXE Engineer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeRemote in Mexico

About the Job

Requirements

  • Seven or more years of hands-on software engineering experience, including two or more years building on Amazon Connect or comparable CCaaS platforms at enterprise scale.
  • Strong, current Amazon Connect skills, including contact flows, routing, Cases and Tasks, Contact Lens, Customer Profiles, Streams API, and the Connect data and analytics stack.
  • Hands-on experience with conversational and generative AI, Amazon Lex, and LLM-based development such as Amazon Bedrock or Q in Connect, including prompt engineering and tool calling.
  • Strong TypeScript, Node.js, and Python skills; production React experience; and solid AWS serverless engineering experience with Lambda, EventBridge, API Gateway, DynamoDB, Step Functions, and Kinesis.
  • Infrastructure as code proficiency with AWS CDK or Terraform, including multi-account deployment patterns.
  • Experience shipping and supporting production systems, testing discipline, observability instrumentation, and incident debugging across the full stack.
  • Current legal authorization to work in the country where the position is located; visa or work permit sponsorship is not available.

Responsibilities

  • Build AI-native self-service using Amazon Connect AI agents, Amazon Q in Connect, and Amazon Bedrock with the Claude model family, implementing multi-agent orchestration with task-specific agents and escalation paths to human queues.
  • Engineer production-scale prompts and tool-calling integrations for SearchProfiles lookups, case creation, external API tools, authentication flows, and guardrails against hallucination and verification loops.
  • Implement barge-in handling, fallback, and error-recovery behavior for voice AI, and validate it with turn-by-turn trace analysis.
  • Optimize inference cost and latency through model-tier selection, prompt caching, and token budgeting against containment-rate targets.
  • Diagnose AI agent performance using observability tooling that correlates contact-flow logs, conversation transcripts, AI agent spans, tool executions, and token usage to isolate latency, cost, and quality issues.
  • Build conversational experiences using intent-based natural language understanding where appropriate, including multilingual support and SSML-tuned voice interactions.
  • Build contact flows integrating AI agents, Lambda-backed business logic, Customer Profiles, and dynamic data-driven routing.
  • Implement Amazon Connect Cases and Tasks solutions, including case templates, queue-based work allocation, SLA/TAT monitoring, approval workflows, and migrations from legacy case systems.
  • Configure and operationalize Contact Lens for real-time sentiment, post-contact summaries, category rules, and quality management.
  • Implement proficiency-based and attribute-driven routing, outbound campaigns with answering machine detection and compliance controls, and workforce management integrations for forecasting, scheduling, and adherence.
  • Build the Amazon Connect analytics data lake using Glue, Lake Formation, and Athena, and build QuickSight dashboards for real-time operations and executive reporting.
  • Support legacy platform migrations from Avaya, Genesys, Cisco, Oracle, and Salesforce through flow conversion, data migration, parallel-run validation, and production cutover on live contact centers.
  • Build custom Agent Workspace experiences with the Amazon Connect Streams API, third-party app embedding, and CRM screen-pop integrations with Salesforce, ServiceNow, Oracle, and custom systems.
  • Build serverless, event-driven backends with Lambda, EventBridge, Step Functions, SQS/SNS, DynamoDB, and Kinesis for real-time event processing and customer journey orchestration.
  • Build accessible components compliant with WCAG 2.1 AA, conduct automated axe-core and Playwright accessibility scanning, and support VPAT/Section 508 documentation for government and enterprise engagements.
  • Author infrastructure as code using AWS CDK with TypeScript as the primary tool, or CloudFormation or Terraform where customer environments require them.
  • Build and maintain CI/CD pipelines using GitHub Actions and automated test suites, including Jest/Vitest unit tests, Playwright end-to-end and API tests, and integration tests against live Connect instances.
  • Follow phased rollout patterns for production contact centers and write runbooks for production cutovers.
  • Instrument monitoring and alerting with CloudWatch metrics, alarms, and custom dashboards across voice, chat, tasks, queues, agents, Lambda, and AI agents, and participate in production incident triage.
  • Apply security and compliance baselines, including least-privilege IAM, DevSecOps scanning, and encryption standards.
  • Work directly with customer engineering teams by pairing on integrations, running technical working sessions, demonstrating completed workstreams, and leading knowledge transfer so customers can operate delivered systems.
  • Contribute to architecture decisions within the workstream, evaluate native Connect capability before custom builds, surface trade-offs to practice leads, and document decisions.
  • Perform code reviews, uphold engineering standards, and mentor junior and mid-level CX engineers through pairing and review feedback.
  • Contribute reusable assets to the practice, including shared CDK constructs, skills/plugins, demo environments, and internal tooling.
  • Support pre-sales as needed by building proof-of-concept demos and providing implementation-grounded input on estimates and SOW technical scope.

Desired Qualifications

  • AWS certifications in Solutions Architect, Developer, or an ML/Connect-relevant Specialty area.
  • Contact center migration experience involving Avaya, Genesys, Cisco, Oracle, or Salesforce to Amazon Connect.
  • Experience in regulated verticals, including government/public sector (Section 508, FedRAMP), healthcare (HIPAA), or financial services.
  • Contact center operations fluency, including workforce management concepts such as forecasting, scheduling, and adherence; quality management; outbound compliance (TCPA); and CX KPIs such as containment, AHT, CSAT, and SLA/TAT.
  • Experience with AI observability, including trace correlation, token/cost attribution, and latency profiling, or accessibility engineering, including WCAG 2.1 AA and axe-core automation.
  • Consulting or client-delivery background.

About the Company

Caylent

AWS-focused cloud-native consulting and DevOps

Caylent is a cloud-native services company that helps organizations maximize the value of AWS-driven solutions. It guides and executes on cloud journeys, offering migration, DevOps, DevSecOps, and ongoing optimization to build, scale, and improve cloud systems. The company uses a co-delivery model, working closely with clients to deliver tailored cloud solutions and transfer knowledge so clients can manage their environments themselves. Caylent differentiates itself with deep AWS alignment (as an AWS all-in partner), a strong library of methodologies and code repositories, and a history rooted in container and microservices work (originating as the first Docker Swarm container-as-a-service platform). Its goal is to shorten time-to-value for customers by applying AWS best practices and proven processes to create scalable, secure, and well-optimized cloud environments.

Company size
501-1,000
Company stage
Growth Equity (Venture Capital)
Total funding
$16.2M
Headquarters
Irvine, CA
Founded
2015

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