AI Engineer Level 4

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, 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., The Lead Software Engineer serves as a senior technical leader responsible for designing, developing, enhancing, and supporting complex software systems that are critical to busine…

• 8 hours ago, The Lead Software Engineer serves as a senior technical leader responsible for designing, developing, enhancing, and supporting complex software systems that are critical to busine…
• 7 hours ago +

• 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, 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, 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

• $122,600-204,400 per year

Jones Lang LaSalle

• Atlanta, GA JLL empowers you to shape a brighter way. Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology fo…