Customer Deployed Engineer

titan-msp; United States; Remote; USD 150,000 - 200,000; Full time

Benefits offered by this job

Remote within the US

Up to 5% travel

Job summary

Titan MSP seeks an engineer to take client workflow ideas from initial assessment through to AI agents running in the client’s environment. You’ll scope the problem, build agents and integrations, deploy them with appropriate access controls, and measure adoption and results.

Success is tied to production use, user uptake, and delivery within the agreed fixed fee. Remote within the US with up to 5% travel is offered, with a base compensation of $150,000–$200,000.

Qualifications

• Four or more years of engineering experience, including client-facing work.
• Experience building and shipping LLM-powered agents and understanding how model behavior affects the user experience.
• Ability to write production-quality code in TypeScript, Python, or a comparable language.
• Familiarity with Microsoft 365 as a data source, including Graph API, SharePoint, Teams, Outlook, and tenant permissions and consent.
• Ability to lead scoping conversations with business leaders, assess use-case value, and write clear project scopes.
• Strong ownership of delivery and a security-minded approach to client data.

Responsibilities

• Join client opportunity assessments and identify workflows that could benefit from connecting information across business systems.
• Define each project’s data sources, agent actions, target users, success measures, baseline, and scope; flag constraints outside the client’s control.
• Build AI agents, connectors, and reusable skills using Microsoft 365 sources such as Graph, SharePoint, Teams, and Outlook, as well as client APIs and MCP servers.
• Deploy within client tenants using least-privilege access, and maintain governance records and documentation suitable for audit or due diligence.
• Measure performance against a baseline, train users, and transition deployed agents into ongoing maintenance.
• Turn effective project components into reusable connectors, evaluations, skills, and templates.

Skills

LLM-powered agents

TypeScript

Python

Microsoft 365 integration

Client-facing

Security-minded delivery

Tools

MCP servers

Graph API

SharePoint

Job description

Role overview

Take client workflow ideas from initial assessment through to AI agents running in the client’s own environment. You’ll scope the problem, build agents and integrations, deploy them with appropriate access controls, and measure adoption and results. Success is tied to production use, user uptake, and delivery within the agreed fixed fee.

Responsibilities

• Join client opportunity assessments and identify workflows that could benefit from connecting information across business systems.
• Define each project’s data sources, agent actions, target users, success measures, baseline, and scope; flag constraints outside the client’s control.
• Build AI agents, connectors, and reusable skills using Microsoft 365 sources such as Graph, SharePoint, Teams, and Outlook, as well as client APIs and MCP servers.
• Deploy within client tenants using least-privilege access, and maintain governance records and documentation suitable for audit or due diligence.
• Measure performance against a baseline, train users, and transition deployed agents into ongoing maintenance.
• Turn effective project components into reusable connectors, evaluations, skills, and templates.

Requirements

• Four or more years of engineering experience, including client-facing work.
• Experience building and shipping LLM-powered agents and understanding how model behavior affects the user experience.
• Ability to write and review production-quality code in TypeScript, Python, or a comparable language.
• Familiarity with Microsoft 365 as a data source, including Graph API, SharePoint, Teams, Outlook, and tenant permissions and consent.
• Ability to lead scoping conversations with business leaders, assess use-case value, and write clear project scopes.
• Strong ownership of delivery and a security-minded approach to client data.

Nice to have

• Forward-deployed, solutions engineering, or sales engineering experience in SaaS, AI, or consulting.
• Experience building MCP servers, connectors, or skills for AI assistants.

Benefits and work setup

• Remote within the US, with up to 5% travel for discovery and launches.
• Listed base compensation is $150,000–$200,000.