GenAI CCAS Application Developer

Opportunity OverviewLeidos is seeking an early-career GenAI Application Developer to build and enhance AI-powered applications for an AWS Contact Center as a Service (CCAS) platform. You will work with Amazon Connect, Lex V2, Amazon Q in Connect, Contact Lens, Bedrock, OpenSearch, and Lambda (Python) to deliver intelligent automation that improves customer experience. 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.You will collaborate 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 maintain privacy and compliance controls. This role offers a direct path to a Leidos full-time position for strong performers.Position DetailsJob TitleGenAI CCAS Application DeveloperProgramFTC SNSLocationRemote — Quarterly travel to Gaithersburg, MDAssignment Duration6+ months (extension possible)Target Start DateFebruary 23, 2026Work HoursStandard (40 hrs/week max)Citizenship RequiredU.S. CitizenSecurity ClearancePublic TrustFTE Conversion PotentialYes — strong performers considered for Leidos full-time rolePrimary ResponsibilitiesAmazon Connect Application DevelopmentBuild, update, and maintain Amazon Connect contact flows, routing profiles, and queues for voice and chat channels.Integrate Lex V2 bots into Amazon Connect flows for call deflection, self-service transactions, and escalation handling.Enable and configure Contact Lens for real-time and post-contact analytics, transcription, summarization, sentiment analysis, and PII 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 & Backend ServicesWrite 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 & ComplianceImplement 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 & Chat IntegrationSupport 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 & OperationsContribute to Git-based CI/CD pipelines, code reviews, and technical 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 QualificationsBachelor’s degree in Computer Science, Engineering, or a related field with 2–4 years of relevant experience; or a Master’s degree with relevant experience.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 multi-channel integration (voice and chat).Experience integrating Lex V2 bots with Amazon Connect flows.Familiarity with conversational AI design principles: 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 articulate technical decisions to teammates.U.S. Citizen with the ability to obtain a Public Trust clearance.Preferred QualificationsPractical 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.Hands-on experience with Amazon Bedrock (LLMs and embeddings) and guardrails, including LLM API calls and prompt engineering.Knowledge of Retrieval-Augmented Generation (RAG) and vector search; AWS OpenSearch Service configuration (VPC, 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.Active AWS certifications such as Developer Associate, Solutions Architect, AI Specialty, DevOps Engineer, or security certs (CISSP/CCSP) are a plus.Hiring ProcessInterview Rounds2 to 3 rounds (phone/video)