AI Enablement Engineer

JOB DESCRIPTION

Duration: 11 months
Location: Atlanta, GA (Hybrid 3 days onsite)




Please source for most skills from below list.

• Anthropic Claude AI
• Anthropic Claude API
• Anthropic Claude Code
• Anthropic Claude Cowork
• Artificial Intelligence (AI)
• Git
• GitHub
• Large Language Models (LLMs)
• Microsoft 365 SharePoint Online
• Microsoft Copilot Studio
• Microsoft Entra ID
• REST API Development
• Security Assertion Markup Language (SAML)
• Snowflake GenAI
  
  
  
  
  Job Description: AI Enablement Engineer
  
  
  
  
  Key Responsibilities
  
  
  
  
  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
  
  
  
  
  Work Environment
  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
  
  
  
  
  Compliance Statement
  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
  evolve based on business needs and the rapid pace of AI tool development.