Description
Description
About This Role
SAIC is looking for a hands-on Principal Engineer to lead the design, build, and delivery of AI-enabled contact center solutions on AWS. You will work at the intersection of conversational AI, enterprise IT service management, and cloud-native architecture — building solutions that transform how organizations deliver IT support to their users.
This is a builder role. You will be writing code, configuring AI pipelines, and deploying integrations in production environments — not directing others to do so. You will also be building solution components that scale across multiple client engagements, creating lasting practice value beyond any single deployment.
If you are currently building on Amazon Connect, AWS Bedrock, and Amazon Q — and you understand how those capabilities connect to enterprise ITSM platforms like ServiceNow — we want to talk to you.
What You'll Do
• Architect and deliver AI-enabled contact center solutions on AWS — from conversational AI design through ITSM integration and compliance reporting
• Build and maintain conversational AI pipelines using Amazon Lex, Bedrock, and Amazon Q — grounded in enterprise IT service management vocabulary and workflow patterns
• Design and implement bidirectional integrations between AWS contact center services and ServiceNow — automated ticket creation, workflow triggers, real-time agent assist, and record enrichment
• Build knowledge management pipelines that keep AI grounding data current as organizational knowledge evolves — ensuring AI responses reflect accurate, up-to-date information
• Implement real-time monitoring and analytics using Amazon Connect Contact Lens — interaction quality, sentiment analysis, SLA tracking, and compliance alerting
• Design automated reporting pipelines that aggregate contact center, AI, and ITSM data into unified compliance and performance dashboards
• Build proactive and agentic capabilities — event-driven architectures that detect and resolve issues autonomously, integrated with enterprise ITSM workflows
• Develop reusable solution assets — intent libraries, integration patterns, automation frameworks, and reporting templates deployable across multiple client environments
• Support client pursuits with technically accurate capability demonstrations and RFP responses
The Environment You'll Work In
• Federal and civilian government IT services — compliance posture and security controls matter in everything you build
• ServiceNow as the primary ITSM backbone — deep integration experience is essential
• Active AWS strategic partnership — you will have access to AWS partner resources, co-sell support, and roadmap visibility
• Multi-client delivery model — what you build for one client should be deployable to the next
• Fast-moving AI landscape — the services you work with are evolving quarterly and you are expected to keep pace
What Makes This Role Different
You are not maintaining someone else's architecture. You are reconstituting and modernizing a solution stack against a materially evolved AWS AI/ML service landscape — then building it into a scalable practice platform.
The intent libraries you build, the knowledge pipelines you design, the integration patterns you establish — these become practice IP that compounds in value across every subsequent client deployment. You are building something that lasts.
Qualifications
What You Bring
Required
• 8–12 years of software engineering or cloud architecture experience
• 4+ years of hands-on AWS production deployment experience
• 2+ years of hands-on Amazon Connect experience in production environments
• Current, active experience with AWS AI/ML services — Bedrock, Amazon Q, Contact Lens — this stack has changed materially in the past 18 months and recency matters as much as total experience
• Demonstrated experience building bidirectional integrations between AWS and ServiceNow in production environments
• Proficiency in Python for Lambda development, automation, and integration engineering
• Working knowledge of ITIL principles — incident, request, change, and knowledge management vocabulary and workflow patterns
• Awareness of FedRAMP compliance requirements and AWS GovCloud vs. commercial region capability differences
• Must be a U.S. Citizen and be able to obtain Public Trust clearance
Core Technical Skills
• Amazon Connect — contact flows, routing, agent desktop, Contact Lens
• AWS Bedrock — foundation model access, prompt engineering, RAG via Knowledge Bases, Bedrock Agents
• Amazon Lex V2 — intent architecture, dialog management, voice and chat channel configuration
• Amazon Q Business — enterprise knowledge orchestration, ServiceNow connector, retrieval pipeline design
• Amazon Kendra — index configuration, data source connectors, relevance tuning
• AWS Lambda, EventBridge, Step Functions, API Gateway — serverless orchestration and event-driven architecture
• ServiceNow — Flow Designer, Integration Hub, REST API, CTI framework configuration
• Amazon CloudWatch, QuickSight — monitoring, alerting, dashboard and reporting design
Preferred
• AWS Certified Solutions Architect, Developer, or Machine Learning certifications
• ITIL Foundation certification or higher
• Experience with Azure OpenAI RBAC configuration
• Familiarity with WEM platform integration with Amazon Connect (NICE, Calabrio, or Verint)
• Background in proactive remediation or AIOps architecture patterns
• Experience building multi-tenant or multi-client solution architectures
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