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Tech Stack
Tools & technologiesAWSJavaJavaScriptNode.jsPythonServiceNowTypeScript
About the role
Key responsibilities & impact- The AI Application Engineer builds the prototypes, services, workflows, and integrations that bring generative AI use cases to life on AWS.
- This is a hands-on role: the engineer pairs directly with the customer's developers in joint build sessions, turning designs into working software while transferring knowledge so the customer's team becomes self-sufficient.
- The work spans Bedrock applications and agents, enterprise integrations, MCP-based tooling, and spec-driven development.
- Build prototypes and pilot-ready services implementing AI use cases on Amazon Bedrock, including RAG and Bedrock Agents.
- Develop APIs, UI components, and workflow integrations connecting AI capabilities to enterprise applications and data sources.
- Build document intake, classification, and extraction workflows using services such as Amazon Textract and Step Functions where relevant.
- Configure and integrate MCP (Model Context Protocol) servers, and work within Kiro spec-driven development workflows, hooks, and steering rules.
- Implement integrations with the Microsoft 365 ecosystem (SharePoint, Outlook/Exchange, Teams, OneDrive) and delivery/observability tools such as ServiceNow, Jira, GitHub, Dynatrace, or Wiz where approved.
- Pair with customer developers in joint build sessions, demonstrating implementation techniques and helping them become self-sufficient.
- Implement guardrails, evaluation tests, and grounding/citation behavior according to the architect's designs.
- Write clean, tested, documented code following reusable development standards, and contribute reusable templates and playbook material.
Requirements
What you’ll need- Strong software engineering skills in a common language such as Python, TypeScript/Node.js, or Java.
- Hands-on experience integrating with LLM or generative AI APIs (Amazon Bedrock preferred) and building RAG or agent-style features.
- Working knowledge of core AWS services for compute, storage, APIs, and identity, including security fundamentals beyond the AI stack.
- Comfort building REST/serverless services, integrations, and automation.
- Experience integrating with enterprise systems via APIs (e.g., Microsoft 365 / Graph, ServiceNow, Jira, GitHub) and handling authentication and access controls.
- Ability to work directly with a customer's developers in a collaborative, pairing-oriented way and contribute to knowledge transfer.
- Good written and verbal communication.
- Experience with MCP server configuration and with Kiro or other spec-driven development tooling (preferred).
- Experience with vector databases, embeddings, and search/retrieval tooling (preferred).
- Familiarity with CI/CD, infrastructure-as-code, and testing best practices on AWS (preferred).
- Exposure to regulated or public-sector environments and responsible-AI / PHI-PII handling (preferred).
- AWS associate-level certification (preferred).
Benefits
Comp & perks- Remote work options
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Software EngineeringAPI DevelopmentDocument Intake WorkflowsIntegration AutomationKiro Spec-Driven DevelopmentVector DatabasesEmbeddingsSearch/Retrieval ToolingCI/CD Best PracticesInfrastructure-as-Code
Soft Skills
CollaborationKnowledge TransferWritten CommunicationVerbal Communication
Certifications
AWS Associate-Level Certification