GenAI CCAS Application Developer

GENAI CCAS Application Developer

The client has an opening for an early career GenAI Application Developer to build and enhance AI-powered applications for an AWS Contact Center As a Service (CCAS) platform that uses Amazon Connect, Lex V2, Amazon Q in Connect, Contact Lens, Bedrock, OpenSearch, and Lambda (Python). This is a software development role focused on conversation flow design, Amazon Connect integrations, AI service orchestration, generative AI safety, and the creation of supporting APIs and data pipelines to improve customer experience through intelligent automation.

You will work with senior developers, UI/UX designers, and cloud engineers to implement features that deflect customer contacts with voice/chat bots, optimize routing and flows, provide agents with real-time AI assistance, and ensure privacy/compliance controls. This is an exciting opportunity to grow your development skills while delivering secure, reliable, and innovative solutions in a mission environment.

Primary Responsibilities

• Amazon Connect application development and configuration:
• Build, update, and maintain Amazon Connect contact flows, routing profiles, and queues to support both voice and chat channels.
• Integrate Lex V2 bots into Amazon Connect flows for call deflection, self-service transactions, and escalation.
• Enable and configure Contact Lens for real-time and post-contact analytics, transcription, summarization, sentiment analysis, and redaction.
• Configure Amazon Q in Connect domains, knowledge sources, guided workflows, and step-by-step agent assist experiences.
• Implement S3-based call and chat transcript storage with encryption, lifecycle policies, and retention compliance.
• AI orchestration and backend services:
• Write AWS Lambda (Python) functions to orchestrate Bedrock LLM calls, embeddings workflows, and model invocation logging.
• Implement OpenSearch indexing, vector/keyword queries, and knowledge synchronization triggers.
• Build retrieval-augmented generation (RAG) pipelines to enhance Amazon Connect agent assist and self-service knowledge.
• Apply structured logging, unit/integration tests, error handling, and performance/cost safeguards.
• Data safety and compliance:
• Implement AI guardrails, prompt templates, and output evaluation for safety and accuracy.
• Enforce PII minimization and redaction policies in Amazon Connect conversation logs.
• Participate in threat modeling and support remediation of findings for contact center integrations.
• Web and chat integration:
• Support CloudFront + WAF configurations for secure web chat entry points.
• Build APIs and event hooks to pass conversation context between web chat, Amazon Connect, and AI services.
• DevSecOps and operations:
• Contribute to Git-based CI/CD pipelines, code reviews, and documentation.
• Maintain runbooks, architecture diagrams, and SOPs for contact flows, bot integrations, and AI workflows.
• Create and monitor CloudWatch dashboards/alarms for call deflection rate, average handle time (AHT), contact resolution, and AI usage metrics.

Basic Qualifications

• Bachelor s degree in Computer Science, Engineering, or related field and 2 4 years of relevant experience; or a Master s with <2 years; or 4 additional years of experience in lieu of a degree.
• 2+ years of software development with Python, including building and troubleshooting AWS Lambda functions.
• Hands-on experience with Amazon Connect setup and configuration, including contact flows, routing profiles, queues, and channel integration (voice, chat).
• Experience integrating Lex V2 bots with Amazon Connect flows.
• Familiarity with conversational AI design, including slot elicitation, error recovery, and safe fallback patterns.
• Infrastructure as Code experience (CloudFormation) and Git-based CI/CD workflows.
• Foundational security knowledge: least privilege IAM, encryption at rest (KMS), and secure logging/monitoring.
• Strong written and verbal communication; able to document designs and explain technical choices to teammates.
• with ability to obtain a Public Trust clearance.

Preferred Qualifications

• Practical exposure to full Amazon Connect deployments, including telephony setup, contact attributes, and queue performance optimization.
• Experience enabling and tuning Contact Lens for compliance, sentiment analysis, and post-contact QA scoring.
• Experience with Amazon Q in Connect for agent assist workflows and knowledge retrieval.
• Experience with Amazon Bedrock (LLM and embeddings) and guardrails; calling LLM APIs and prompt engineering.
• Knowledge of Retrieval Augmented Generation (RAG) and vector search; AWS OpenSearch Service configuration (VPC only, KMS) and k-NN/HNSW indices.
• Familiarity with KMS key policies, grants, and cross-account access; S3 data protection (BPA, lifecycle, access points).
• Experience with AWS WAF, CloudFront, and edge security patterns.
• Observability and analytics skills: CloudWatch dashboards/alarms, X-Ray, Athena/Glue.
• Understanding of privacy/compliance considerations (PII redaction, data retention), and familiarity with FISMA and FedRAMP concepts as applied to contact centers.
• Certifications (any of): AWS Developer Associate, AWS Solutions Architect Associate/Professional, AWS AI Specialty, AWS DevOps Engineer, CISSP/CCSP.