AI Implementation Engineer

Senior AI Implementation Engineer 

Redapt Inc. is a pioneering world-class data center infrastructure integrator, technology engineering firm, and cloud services provider. Our teams focus on delivering innovative solutions and services that power our customers' most demanding applications and enable them to extract powerful insights from data that drive true business value.  

We are looking for a Senior AI Implementation Engineer to join our Cloud Solutions team, with a focus on building and deploying generative AI solutions on AWS using Amazon Bedrock. This individual will translate customer needs into secure, reliable applications that deliver measurable business value.

Our engineers own delivery from discovery and prototyping through production deployment and support. They combine hands-on software engineering, enterprise data integration, and practical AI implementation to build document processing, knowledge retrieval, and workflow automation solutions for our clients.

Responsibilities

• Design, develop, test, and deploy AI applications using Amazon Bedrock foundation models and AWS services.
• Build retrieval-augmented generation (RAG) solutions using Amazon Bedrock Knowledge Bases or custom retrieval pipelines, including ingestion, chunking, embeddings, vector search, and source citations.
• Implement AI agents and tool integrations that connect models to enterprise APIs and workflows, with explicit permissions, validation, and human approval where needed.
• Develop prompts and structured extraction workflows for document understanding, classification, summarization, and business process automation.
• Build Python services and APIs that integrate AI capabilities with customer applications, databases, and enterprise data sources.
• Create representative evaluation datasets and automated tests to measure accuracy, grounding, extraction quality, and agent task completion; validate changes before release.
• Implement layered AI safeguards using Amazon Bedrock Guardrails, IAM, encryption, data access controls, output validation, and protections against prompt injection.
• Automate infrastructure and application delivery using infrastructure as code, Git, CI/CD, versioned prompts and configurations, and repeatable deployments.
• Monitor and troubleshoot production AI workloads; optimize model selection, token usage, latency, reliability, and cost, with retry and fallback strategies.
• Translate customer requirements into solution designs and implementation plans; deliver demonstrations, document decisions, and support operational handoff.

Skills you bring with you