Job description

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 Strong Python and software engineering skills, including API development, automated testing, debugging, code review, and maintainable application design. Hands-on experience implementing applications with Amazon Bedrock, including model invocation, prompt design, inference settings, and integration through AWS SDKs. Practical experience with RAG, embeddings, vector stores, retrieval quality, and grounding responses in enterprise data, including Amazon Bedrock Knowledge Bases. Experience building agent workflows and tool calling, with schema validation, controlled execution, error handling, and integration with external systems. Experience with supporting AWS services such as Lambda, S3, API Gateway, Step Functions, SQS, and CloudWatch, plus SQL and data integration fundamentals. Understanding of AI evaluation, hallucination risks, security, and data privacy; hands-on experience with IAM and infrastructure as code using Terraform, AWS CDK, or CloudFormation. Qualifications BS or MS in Computer Science, Information Systems, Engineering, or a related field preferred; equivalent experience considered. 5+ years of experience in software engineering, cloud application development, data engineering, or related roles, with hands-on responsibility for production systems. Demonstrated experience delivering generative AI applications from prototype to production, including hands-on implementation using Amazon Bedrock and AWS. Additional experience we value Amazon Bedrock Agents and production agent orchestration, including tool integration, state management, observability, and controlled access to enterprise systems. Intelligent document processing using Amazon Bedrock Data Automation, Amazon Textract, or model-based extraction, with normalization, validation, and source traceability. Vector search and retrieval implementations using Amazon OpenSearch or PostgreSQL with pgvector, including metadata filtering and retrieval tuning. AI delivery practices such as evaluation pipelines, prompt and model versioning, regression testing, staged releases, rollback, and production quality monitoring. Effective use of AI coding assistants, with independent validation of generated code, automated tests, and adherence to customer security and development standards. Consulting and technical leadership skills, including customer discovery, engineering mentorship, and clear communication of quality, security, performance, and cost tradeoffs. Travel required Travel typically 5% or less a year Equal Employment Opportunity: Redapt is an equal opportunity employer. Applicants will not be discriminated against because of race, color, creed, sex, sexual orientation, gender identity or expression, age, religion, national origin, citizenship status, disability, ancestry, marital status, veteran status, medical condition, or any protected category prohibited by local, state, or federal laws. All employment is decided based on qualifications, merit, and business need. #LI-TS1

Requirements

Must-haves

Senior AI Implementation Engineer
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
Strong Python and software engineering skills, including API development, automated testing, debugging, code review, and maintainable application design.
Hands-on experience implementing applications with Amazon Bedrock, including model invocation, prompt design, inference settings, and integration through AWS SDKs.
Practical experience with RAG, embeddings, vector stores, retrieval quality, and grounding responses in enterprise data, including Amazon Bedrock Knowledge Bases.
Experience building agent workflows and tool calling, with schema validation, controlled execution, error handling, and integration with external systems.
Experience with supporting AWS services such as Lambda, S3, API Gateway, Step Functions, SQS, and CloudWatch, plus SQL and data integration fundamentals.
Understanding of AI evaluation, hallucination risks, security, and data privacy; hands-on experience with IAM and infrastructure as code using Terraform, AWS CDK, or CloudFormation.
5+ years of experience in software engineering, cloud application development, data engineering, or related roles, with hands-on responsibility for production systems.
Demonstrated experience delivering generative AI applications from prototype to production, including hands-on implementation using Amazon Bedrock and AWS.
Additional experience we value
Amazon Bedrock Agents and production agent orchestration, including tool integration, state management, observability, and controlled access to enterprise systems.
Intelligent document processing using Amazon Bedrock Data Automation, Amazon Textract, or model-based extraction, with normalization, validation, and source traceability.

Nice-to-haves

BS or MS in Computer Science, Information Systems, Engineering, or a related field preferred; equivalent experience considered.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiawspythonci/cdapisql

Platform: greenhouse
Effort: quick