AI Application Engineer
Role Summary
Key Responsibilities
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.
Required Qualifications
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.
Preferred Qualifications
Experience with MCP server configuration and with Kiro or other spec-driven development tooling.
Experience with vector databases, embeddings, and search/retrieval tooling.
Familiarity with CI/CD, infrastructure-as-code, and testing best practices on AWS.
Exposure to regulated or public-sector environments and responsible-AI / PHI-PII handling.
AWS associate-level certification.
Location & Travel
This is a US-only position; candidates must be authorized to work in and based in the United States.
The role is primarily remote but may require travel up to 10% to 15% during the engagement for on-site workshops and customer sessions.
Experience Level
5 to 10 years experience with at least 2 years of relevant technical stack experience.