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Senior Full Stack Agentic AI Developer

CapNexus
CompanyCapNexus
CategoryEngineering
LocationRemote
RemoteRemote
EmploymentNot stated
LevelSenior
SalaryNot stated by the employer
Posted27 May 2026
Last verified30 Jul 2026
SourceEmployer career page (greenhouse)
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Description
Capnexus is a comprehensive services provider. Our team consists of outstanding professionals, highly experienced in designing, building, and supporting retail software. We see ourselves as a build-as-a-service provider who follows a repeatable business pattern that can be applied to a variety of platforms and verticals. Having a culture built on outcomes and delivery at the core of the business, Capstone is providing its customers with a complete suite of services for software development, system analysis, integration, implementation, and support, as well as the option to engage a single team to perform all the services they require.   Who You Are and What You’ll Do: CapNexus is looking for a highly skilled Senior Full Stack Agentic AI Developer specializing in AWS serverless architecture and Amazon Bedrock agentic AI to join our growing team. This is an exciting opportunity to work on cutting-edge generative AI and agentic solutions that transform how enterprise customers engage with their data, automate intelligent workflows, and deliver personalized customer experiences at scale.   Responsibilities: Design and implement agentic workflows using Amazon Bedrock Agent Core, including Agent Core Runtime for agent execution and Agent Core Gateway for API exposure, action groups, and Lambda-backed tool use. Build agents for real-world customer-facing use cases — reservation bookings, service requests, customer-assist chat and voice — integrated with Amazon Connect for omnichannel delivery. Implement RAG pipelines using Knowledge Bases for Bedrock, including embedding model selection, chunking strategy, and retrieval quality optimization. Design and develop serverless backend services using AWS Lambda, Step Functions, EventBridge, and API Gateway. Build, debug, and maintain Lambda functions in production using Lambda Powertools, structured logging, CloudWatch Logs Insights, and X-Ray tracing for observability and performance optimization. Design and develop the Customer 360 API layer to expose unified customer profiles and CDP outputs to downstream applications and dashboards. Build responsive UI/UX for customer-facing and internal applications including the Customer Portal, preference management center, and campaign management interfaces using React. Develop and maintain bi-directional integration with NetSuite for lead creation, contact synchronization, and opportunity management. Implement integrations with third-party platforms including Camp Spot, Office 365, Zoom Phones, and Amazon Connect to support omnichannel workflows. Build customer journey tracking features and front-end components to visualize lifecycle analytics and engagement data. Implement the customer preference management center supporting opt-in/opt-out, communication preferences, and data compliance workflows (GDPR right-to-forget, right-to-access). Consume SageMaker and Bedrock model outputs to surface AI-driven insights — lead scoring, audience segmentation, hyper-personalization — within applications. Collaborate with Data/ML and DevOps/MLOps engineers to ensure seamless end-to-end data flows from back-end pipelines to front-end interfaces. Support UAT for application features and contribute to technical documentation.   Qualifications: 5+ years of full stack development experience with demonstrated depth on the backend. Hands-on experience building agentic workflows on Amazon Bedrock Agent Core — specifically Agent Core Runtime and Agent Core Gateway — not surface-level familiarity. This is a hard requirement. Demonstrated ability to design agent action groups, tool use patterns, and multi-step agent reasoning flows for real production use cases. Experience implementing RAG architectures: embedding models, chunking strategy, Knowledge Bases for Bedrock, retrieval quality tuning. Deep hands-on experience with AWS serverless services: Lambda
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