Contract - Senior CXE Engineer - Amazon Connect in City of London

3 x Contract Senior CXE Engineer - Amazon Connect

Day Rate - DoE

Contract Length - Initial 6 months - Rolling extensions

UK Remote based - Some travel for essential meetings

Candidates must be eligible to work and reside in the UK

About the Role

You will spend the majority of your time in code and in the AWS console: building contact flows and AI agents, writing Lambda functions and CDK stacks, developing React-based agent and admin tooling, and debugging production issues on systems that serve tens of thousands of agents and millions of customer interactions. You work within architectures set by practice leads, and you're expected to pressure-test them, propose better patterns, and own the implementation quality of your workstream from first commit through production cutover. This role blends deep Amazon Connect platform engineering, generative AI development on Bedrock and Claude, and full-stack serverless work, with regular direct interaction with customer engineering teams.

Responsibilities

• AI Agent & Conversational AI Development
  • Build AI-native self-service using Amazon Connect AI agents, Amazon Q in Connect, and Amazon Bedrock (Claude model family), implementing multi-agent orchestration patterns, orchestrator agents delegating to task-specific agents with escalation paths to human queues.
  • Engineer prompts and tool-calling integrations at production scale: SearchProfiles lookups, case creation, external API tools, authentication flows, and guardrails against hallucination and verification loops.
  • Implement barge-in handling, fallback, and error-recovery behaviour for voice AI, and validate it with turn-by-turn trace analysis.
  • Optimize inference cost and latency hands-on: model tier selection (Haiku vs. Sonnet vs. Opus), prompt caching, and token budgeting against containment-rate targets.
  • Diagnose AI agent performance using observability tooling (agent spans, and CloudWatch) 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 where intent-based NLU is the right fit, including multilingual support and SSML-tuned voice interactions.
• Amazon Connect Platform Engineering
  • Build contact flows that integrate AI agents, Lambda-backed business logic, Customer Profiles, and dynamic data-driven routing.
  • Implement Amazon Connect Cases and Tasks solutions: 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, and workforce management (WFM) integrations for forecasting, scheduling, and adherence (FCS).
  • Build out the Amazon Connect analytics data lake (Glue, Lake Formation, Athena) and QuickSight dashboards for real-time operations and executive reporting.
  • Support legacy platform migrations (Avaya, Genesys, Cisco, Oracle, Salesforce): flow conversion, data migration, parallel-run validation, and production cutover on live contact centers.
• Full-Stack & Portal Engineering
  • Build custom Agent Workspace experiences with the Amazon Connect Streams API, third-party app embedding, and CRM screen-pop integrations.
  • Build serverless, event-driven backends with Lambda, EventBridge, Step Functions, SQS/SNS, DynamoDB, and Kinesis for real-time event processing and customer journey orchestration.
  • Treat accessibility as a first-class requirement: WCAG 2.1 AA compliant components, automated axe-core/Playwright accessibility scanning, and support for VPAT/Section 508 documentation on government and enterprise engagements.
• Infrastructure, Delivery & Quality
  • Author infrastructure as code with AWS CDK (TypeScript) as the primary tool and CloudFormation or Terraform where customer environments require them.
  • Build and maintain CI/CD pipelines (GitHub Actions) and automated test suites: Jest/Vitest unit tests, Playwright E2E and API tests, and integration tests against live Connect instances.
  • Follow phased rollout patterns for production contact centers where downtime is measured in missed calls; write the runbooks that make cutovers boring.
  • Instrument monitoring and alerting (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 in everything you ship: least-privilege IAM, DevSecOps scanning, encryption standards.
• Collaboration & Practice Contribution
  • Work directly with customer engineering teams: pair on integrations, run technical working sessions, demo completed workstreams, and lead knowledge transfer so customers can operate what you build.
  • Contribute to architecture decisions within your 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 back to the practice, shared CDK constructs, skills/plugins, demo environments, and internal tooling, so the next engagement starts further ahead.

Qualifications

• Hands-on software engineering experience, including building on Amazon Connect or comparable CCaaS platforms at enterprise scale.
• Strong, current Amazon Connect skills: contact flows, routing, Cases and Tasks, Contact Lens, Customer Profiles, Streams API, and the Connect data/analytics stack.
• Hands-on experience with conversational and generative AI, Amazon Lex plus LLM-based development, including prompt engineering and tool calling.
• Strong TypeScript/Node.js and Python; production React experience; solid AWS serverless engineering.
• 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.