Min
USD $150,000.00/Yr. Max
USD $175,000.00/Yr. Position Overview

SCOPE OF ROLE:

The AI Engineer builds the standards, tools, and controls that help S:US move AI solutions from experimentation into reliable use. Reporting to the Vice President, Apps, Data & AI, this role partners across IT to deliver secure, reusable, and cost-effective AI capabilities that support the S:US mission.

 

KEY RESPONSIBILITIES:

AI Engineering & Platform Development

• Build and improve the AI development environment including GitHub, VS Code, GitHub Copilot, Azure, agents, and approved integrations.
• Design reusable patterns for agent workflows, multi-agent coordination, MCP integrations, testing, and review.
• Evaluate emerging AI development tools and recommend those that fit S:US’s Microsoft-first environment.
• Integrate AI solutions with enterprise platforms and APIs so workflows operate reliably from end to end.

Quality, Security & Responsible AI

• Build testing and evaluation practices for AI-generated output, including automated checks and human review for higher-risk changes.
• Apply responsible AI, privacy, and security requirements to agent workflows and AI tools.
• Protect PHI and other sensitive client, employee, and business data through appropriate access, masking, redaction, and approval controls.
• Partner with IT Operations & Security to manage prompt injection, permissions, third-party tools, secrets, and software supply chain risks.

DevSecOps, Monitoring & Cost Management

• Build and strengthen CI/CD pipelines using GitHub Actions, Azure DevOps, and Azure.
• Embed automated testing, security scanning, and quality checks into the software delivery process.
• Monitor agent performance, reliability, latency, token usage, and cost.
• Use performance and cost data to improve models, workflows, and platform decisions.

Collaboration & Enablement

• Partner with Applications, Data, Analytics, IT Infrastructure & Security, and PMO to apply shared AI standards and improve delivery.
• Create practical playbooks, training, and office hours that help teams use AI engineering tools effectively.
• Translate emerging AI capabilities into clear recommendations, standards, and practices that teams can adopt.

Qualifications

REQUIRED QUALIFICATIONS

• Five or more years of professional software engineering experience in cloud-based environments.
• Hands-on experience building agentic AI solutions, including agent workflows, prompt design, and tool or API integrations.
• Strong knowledge of Microsoft Azure and experience with GitHub Actions or Azure DevOps.
• Experience building secure CI/CD pipelines with automated testing, security scanning, and quality checks.
• Experience evaluating AI output and applying responsible AI, privacy, and security controls.
• Strong full-stack engineering, API integration, automated testing, version control, and code review skills.
• Working knowledge of observability and monitoring tooling (Azure Monitor, Application Insights) and delivery/issue-tracking platforms (e.g., Jira).

Excellent communication and collaboration skills, with the ability to turn emerging AI capabilities into practical solutions.

 

PREFERRED QUALIFICATIONS

• Experience with LLMOps or agent observability tooling, including tracing, token spend monitoring, and model routing/fallback, in a production setting.
• Experience in a regulated enterprise technology environment, including direct exposure to PHI-handling or HIPAA compliance requirements.
• Familiarity with Jira or similar modern agile delivery tooling used to plan, track, and orchestrate engineering work.
• Experience standing up an AI or platform engineering capability from the ground up, ideally as an early or founding technical hire.

ID2026-18997 Work LocationIn Person