AI Application Engineer wtih AWS Bedrock

AI Application Engineer wtih AWS Bedrock

Posted Today by Brilliant Infotech Inc.

Negotiable
Undetermined
Remote
Remote

Summary: The AI Application Engineer role focuses on developing prototypes and services that implement generative AI use cases on AWS, specifically utilizing Amazon Bedrock. This hands-on position involves collaborating directly with customer developers to create working software while facilitating knowledge transfer for self-sufficiency. The engineer will work on various integrations and workflows, ensuring the delivery of robust AI solutions. The role requires a strong technical background and the ability to engage in joint build sessions with clients.

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.

Key Skills:

  • 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.

Salary (Rate): undetermined

City: undetermined

Country: United States

Working Arrangements: remote

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT

Detailed Description From Employer:

Job Title : AI Application Engineer – AWS Bedrock

Hire type: Contract.

Location: 100% Remote

Note: Need W2 Candidates Only

Role Summary

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.

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.