Senior Development Lead - Advanced RPA

Job Summary

Senior AWS Connect & CX AI Engineer

Role Overview

We are seeking a hands-on AWS Connect & CX AI Engineer to design, build, and maintain reusable customer experience demonstrations on AWS -Amazon Connect as the core contact center platform.

This role combines Amazon Connect engineering, conversational AI, generative AI, backend integration, analytics, and demo development. The primary objective is to create client-ready solutions that can be rapidly configured for RFPs, pursuits, workshops, and industry-specific CX use cases.

The ideal candidate can independently translate a business use case into a working AWS demonstration, explain the architecture to business and technical stakeholders, and document the solution for reuse by other team members.

Key Responsibilities

Key Responsibilities 1. Amazon Connect Administration & Omnichannel Configuration Configure and administer Amazon Connect instances, users, security profiles, queues, routing profiles, hours of operation, phone numbers, and agent workspace. Design and develop contact flows for inbound and outbound customer journeys. Configure voice and chat capabilities and integrate email, SMS, and WhatsApp use cases where supported by the selected architecture. Configure agent, supervisor, recording, monitoring, and reporting experiences. Set up and demonstrate Tasks, Cases, Customer Profiles, and outbound engagement capabilities where applicable. 2. Conversational AI & Customer Self-Service Develop Amazon Lex voice and chat bots using intents, slots, prompts, validation, fulfilment, and fallback logic. Build conversational IVR and self-service journeys for authentication, intent discovery, knowledge retrieval, transaction completion, confirmation, and escalation. Design controlled handoff from bots to human agents with relevant customer and interaction context. Create reusable conversational components, prompts, business rules, and industry-specific customer journeys. 3. Generative AI, Agent Assist & Agentic AI Configure Amazon Q in Connect for knowledge recommendations, contextual guidance, suggested responses, interaction summaries, and after-contact work. Develop generative AI solutions using Amazon Bedrock, knowledge bases, retrieval-augmented generation, prompt engineering, guardrails, and validation controls. Build AI agents for customer self-service, agent assistance, workflow execution, and exception handling. Design MCP-enabled tools or equivalent service interfaces that allow AI agents to retrieve information and execute approved actions. Implement human-in-the-loop controls, confirmation steps, and traceability for agentic workflows. 4. AWS Integration & Development Develop backend business logic and integrations using AWS Lambda, API Gateway, DynamoDB, S3, and CloudWatch. Integrate Amazon Connect journeys with mock or enterprise CRM, case management, order management, billing, appointment, and service management systems. Develop secure REST API and event-driven integration patterns with appropriate IAM and access controls. Use Python for backend development and automation; working knowledge of Node.js or TypeScript is preferred. Apply source control, deployment, monitoring, logging, and troubleshooting practices across demo assets. 5. Conversation Analytics & Quality Monitoring Configure Contact Lens for transcription, conversation analytics, sentiment analysis, contact themes, keyword detection, and interaction search. Build demonstrations for automated quality evaluation, compliance checks, contact-driver analysis, interaction summaries, and supervisor insights. Create dashboards and outputs that explain self-service completion, transfer reasons, customer themes, and operational opportunities. Validate analytics outputs and clearly document assumptions, limitations, and data dependencies. 6. Demo Factory Development & Presales Support Build reusable AWS CX demo environments and accelerators that can be configured for retail, banking, utilities, healthcare, telecom, education, and other industries. Develop end-to-end demonstrations covering self-service, human handoff, agent assist, workflow completion, conversation analytics, and reporting. Partner with CX transformation, solution, engineering, sales, and presales teams to convert client requirements into credible demonstrations. Create demo scripts, architecture diagrams, sample data, configuration guides, deployment documentation, runbooks, and troubleshooting guides. Support RFP responses, client workshops, technical walkthroughs, and live demonstrations. Document security considerations, production dependencies, known limitations, and assumptions without overstating demo readiness. 7. Engineering Ownership & Reusability Own the design, build, test

Skill Requirements

Required Qualifications

• 4–18 years of overall experience in cloud application development, contact center technology, conversational AI, or related engineering roles.
• Strong hands-on experience administering and developing solutions on Amazon Connect.
• Practical experience building voice and chat bots using Amazon Lex.
• Experience with Amazon Q in Connect and Contact Lens, including agent assistance, knowledge recommendations, analytics, or quality use cases.
• Hands-on AWS development experience using Lambda, API Gateway, DynamoDB, S3, CloudWatch, IAM, and REST APIs.
• Working knowledge of Amazon Bedrock, prompt engineering, RAG architectures, knowledge bases, guardrails, and AI agent patterns.
• Strong Python development capability; exposure to Node.js or TypeScript is preferred.
• Experience integrating contact center solutions with CRM, case management, order, billing, or service platforms.
• Ability to independently design, build, test, demonstrate, document, and troubleshoot an end-to-end solution.
• Good understanding of contact center operations, customer journeys, routing, quality monitoring, and operational reporting.
• Bachelor’s degree in computer science, Engineering, Information Technology, or a related discipline, or equivalent practical experience.

Other Requirements

Preferred Qualifications

• Experience building reusable demo environments, proof-of-concepts, solution accelerators, or presales prototypes.
• Exposure to Model Context Protocol (MCP), tool calling, multi-agent orchestration, or similar agent integration patterns.
• Experience with Amazon Connect Customer Profiles, Cases, Tasks, outbound campaigns, and related workforce or quality capabilities.
• Knowledge of OpenSearch, Bedrock Knowledge Bases, Step Functions, SNS, SQS, CloudFormation, AWS CDK, or Terraform.
• Integration experience with Salesforce, ServiceNow, or comparable enterprise platforms.
• Relevant AWS certifications in Solutions Architecture, Development, Machine Learning, or related areas.
• Experience supporting client workshops, technical presentations, RFPs, and live demonstrations.

Behavioural Competencies

• Strong hands-on ownership and delivery orientation
• Structured problem-solving and solution design capability
• Ability to operate independently in an evolving presales environment
• Clear communication with business and technical stakeholders
• Ability to convert requirements into practical and demonstrable customer journeys
• Strong collaboration across transformation, sales, architecture, and engineering teams
• Focus on reusability, documentation, reliability, and technical credibility