About the role

Role Summary

Early-career GenAI CCAS Application Developer to build and enhance AI-powered applications that support an AWS Contact Center as a Service (CCAS) platform for the FTC SNS program. You’ll develop secure, scalable solutions using Amazon Connect, Amazon Lex V2, Amazon Q in Connect, Bedrock, OpenSearch, and AWS Lambda.

Responsibilities

Build and maintain Amazon Connect contact flows, routing profiles, and queues for voice and chat
Integrate Amazon Lex V2 bots into Amazon Connect for self-service, call deflection, and escalation
Configure/support Amazon Contact Lens for analytics including transcription, summarization, sentiment, and PII redaction
Configure Amazon Q in Connect (domains, knowledge sources, guided workflows, agent assist)
Implement encrypted S3 storage for transcripts with lifecycle and retention policies
Develop AWS Lambda functions in Python to orchestrate Amazon Bedrock LLM calls and embeddings workflows (with invocation logging)
Build RAG pipelines using Amazon Bedrock and OpenSearch
Configure OpenSearch indexing (vector + keyword search) and knowledge synchronization
Implement AI safety features: guardrails, prompt templates, output validation, and safety controls
Enforce PII minimization/redaction for conversation logs
Support CloudFront and AWS WAF for secure web chat entry points
Develop APIs and event integrations connecting web chat, Amazon Connect, and AI services
Participate in Git-based CI/CD, code reviews, testing, and documentation
Create/maintain runbooks, SOPs, and architecture documentation
Monitor performance with CloudWatch dashboards/alarms; track operational metrics (deflection, AHT, resolution, AI usage)

Required Technical Skills

Bachelor’s in CS/Engineering (or equivalent experience); 2–4 years software development (or Master’s with applicable experience)
2+ years Python development
Experience with AWS Lambda development/troubleshooting
Hands-on Amazon Connect (contact flows, routing profiles, queues, voice/chat integration)
Experience integrating Amazon Lex V2 with Amazon Connect
Conversational AI knowledge (slot elicitation, error recovery, safe fallback)
CloudFormation IaC experience
Git-based CI/CD experience
Understanding of IAM least privilege, AWS KMS encryption, and secure logging/monitoring
Strong communication skills
U.S. citizenship and ability to obtain Public Trust clearance

Preferred / Nice-to-Have

Enterprise Amazon Connect deployments
Amazon Contact Lens
Amazon Q in Connect
Amazon Bedrock, LLM APIs, prompt engineering, guardrails
RAG experience
AWS OpenSearch (vector search, k-NN/HNSW)
Knowledge of AWS KMS key policies and S3 security/lifecycle

About Aptonet

Aptonet provides technology and engineering services supporting federal and enterprise missions, including secure cloud and application development. The posting indicates work focused on building AI-powered customer service solutions on AWS for a government program.