AI Enablement Engineer

Claude Platform Implementation

Build, test, and deploy MCP (Model Context Protocol) servers that give Claude access to

Organization's enterprise systems

Author and publish Claude skills and plugins for workflows across Engineering, Operations,

Finance, and other business units

Write and maintain system prompts, CLAUDE.md files, and organizational AI context that shape

how Claude behaves across Organization

Configure and administer Claude Code and Cowork deployments for engineering and business

teams

Build connectors to internal data sources, SharePoint libraries, Confluence spaces, and third

party APIs

Iterate on implementations based on real usage fix what doesn't work, improve what does

Microsoft Copilot Implementation

Build custom Copilot Studio agents and copilots tailored to our team workflows

Develop Copilot connectors and plugins that surface internal data within M365 Copilot

Extend M365 Copilot capabilities using Microsoft Graph API, Power Automate, and SharePoint

connectors

Configure Copilot experiences in Teams, Outlook, Word, and Excel for targeted business units

Build Declarative Agents and API plugins using OpenAPI specs for enterprise system access

Kiro & Developer Tooling

Deploy and configure AWS Kiro for Organization's engineering teams

Write Kiro hooks, spec files, and steering configurations that align AI coding assistance with

Organization's standards and patterns

Integrate Kiro into existing CI/CD pipelines and code review workflows

Build reusable templates and patterns that accelerate developer onboarding to Kiro

Coordinate with engineering leads to identify and prioritize high-value use cases

Integration & Automation Engineering

Wire AI platforms to enterprise systems (ServiceNow, Jira, Salesforce, Workday, Veeva,

Snowflake) via REST APIs, webhooks, and MCP

Build automation workflows that connect AI-generated outputs to downstream business actions

Maintain integration code in GitHub with proper versioning, branching, and documentation

Debug and remediate broken integrations; monitor pipelines and respond to failures

Operations & Reliability

Monitor AI tool usage, API costs, token consumption, and performance across all platforms

Manage authentication credentials, API keys, and OAuth app registrations for AI services

Apply platform updates, configuration changes, and patches as tools evolve

Maintain runbooks and troubleshooting guides so issues get resolved fast

Track and report on adoption metrics and usage patterns

Hands-On Enablement

Embed with business and engineering teams to understand their actual workflows, not just their

stated requirements

Build the specific tools, templates, and configurations that unlock productivity not slide decks

about it

Rapidly prototype, test, and iterate; ship working solutions over perfect ones

Write clear technical documentation for everything you build

Required Qualifications

3+ years in software engineering, integration engineering, or platform engineering with a

track record of building and shipping things

Hands-on proficiency in Python and/or JavaScript/TypeScript

Experience building and consuming REST APIs, webhooks, and event-driven integrations

Demonstrated, practical experience deploying AI tools (LLMs, agents, or copilots) in a real

environment not just experimenting

Experience with the Microsoft 365 ecosystem: SharePoint, Teams, Graph API, and Power

Platform

Git and GitHub proficiency you version-control everything you build

Strong debugging and troubleshooting skills; you diagnose before you escalate

Preferred Qualifications

Direct experience building or configuring MCP (Model Context Protocol) servers

Hands-on experience with Anthropic Claude: Claude API, Claude Code, or Cowork

Experience building in Microsoft Copilot Studio (Declarative Agents, API plugins, custom

connectors)

Experience with AWS Kiro or comparable AI-native development environments

Experience building Power Automate flows and Power Platform solutions for enterprise

workflows

Familiarity with Microsoft Entra ID, OAuth 2.0, SAML, and enterprise authentication patterns

Experience with enterprise systems commonly integrated with AI: ServiceNow, Jira, Salesforce,

Snowflake, Confluence

Experience in financial services or other regulated industries (PCI DSS, SOX, GLBA

awareness)

Familiarity with prompt engineering, RAG patterns, and LLM context management

What Success Looks Like

This is a delivery role. Success is measured by what ships and what gets used, not by planning or

analysis.

MCP servers operational and actively used by Organization's teams, with clear ownership and

documentation

Claude skills and Copilot agents in production, reducing time-on-task for targeted workflows

Kiro configured and adopted by engineering teams, with measurable impact on development

workflows

Integrations between AI tools and enterprise systems running reliably with defined SLAs

Short cycle time from request to working solution teams get what they ask for quickly

High tool adoption rates driven by solutions that actually solve real problems

Zero surprise outages monitoring, alerting, and runbooks are in place before issues happen

Reporting Structure

Reports to: Director / Senior Director, Infrastructure & Platform Engineering

Key Partners: Engineering, IT Operations, Security, Data Engineering, Product, and Business

Unit leads

Hybrid or remote work environment aligned with Organization's policies

Cross-functional collaboration across U.S., India, and Philippines teams

Fast-paced environment where priorities shift as AI tools evolve rapidly adaptability is

essential

This position operates within a regulated financial services environment. All responsibilities must be

performed in accordance with Organization's policies, procedures, and applicable regulatory requirements, including but not limited to PCI DSS, SOX, and GLBA. Duties and responsibilities may