Principal AI Operations Engineer

Location: Home based remote role associated with Oak Brook, Illinois, United States; relocation is not provided.

Salary: $152,700–$220,000 per year.

Company

hirify.global provides health and wealth solutions, including automatic rollover services, health savings accounts, emergency savings, and custody services, serving more than 7 million clients and managing over $62 billion in assets.

What you will do

• Define enterprise telemetry, logging, observability, retention, redaction, masking, and access standards for AI systems, including traces, prompts, tool calls, retrieval, tokens, latency, and cost.
• Build integrations across AI applications, agent platforms, vendor AI, enterprise logging, application performance monitoring, security monitoring, alerting, incident response, governance, risk, compliance, and cost-management platforms.
• Design evaluation frameworks with golden datasets, offline evaluation harnesses, automated and LLM-as-judge scoring, regression gates, drift detection, and monitoring for vendor model changes.
• Build runtime guardrails for agents, including authorization, scope and spend limits, escalation paths, human-in-the-loop triggers, and hard-stop conditions.
• Translate NIST AI RMF, ISO/IEC 42001, model risk management, privacy, and recordkeeping obligations into operational controls, audit evidence, incident processes, and continuous compliance monitoring.
• Maintain the AI system inventory, define metrics for usage, quality, cost, and risk, optimize token and platform spend, and coach teams through fully instrumented AI deployments.

Requirements

• Bachelor of Science in Engineering or Computer Science.
• At least 8 years of telemetry-driven engineering experience, including at least 2 years operating LLM, ML, or agentic systems in production with hands-on ownership of instrumentation and monitoring.
• Production-grade proficiency in Python and SQL for building tooling, pipelines, and services used by other teams.
• Experience with AI evaluation and observability, including evaluation harnesses, tracing, scoring, drift detection, and guardrails.
• Working command of at least one AI risk or governance framework, such as NIST AI RMF, ISO/IEC 42001, EU AI Act, or model risk management practice, with the ability to convert it into controls and code.
• Experience operating in a regulated environment where logging, retention, evidence, and access control are enforced.
• Ability to influence engineering teams, legal counsel, and executive stakeholders without formal authority.
• Ability to occasionally work outside normal business hours for project deadlines and to work for prolonged periods at a desk and computer.

Nice to have

• Datadog Certified Professional, Google Cloud Professional Data Engineer for BigQuery ML, or PagerDuty’s AI Ops certification.
• Experience in financial services, healthcare, benefits administration, or another regulated industry handling PHI, PII, or fiduciary data.
• Deep knowledge of telemetry platforms and metric and measurement practices.
• Hands-on experience with enterprise AI and application observability, centralized logging, governance, risk, continuous compliance monitoring, AI inventory, evaluation and testing, incident management, and cloud cost management.
• FinOps or cloud cost management experience applied to token and inference spend.
• AI security knowledge, including prompt injection defense, OWASP LLM and agentic risk categories, red teaming, tool sandboxing, and least-privilege agent identity design.
• Experience establishing a capability that other teams adopted voluntarily.

Culture & Benefits

• Home-based remote work.
• Healthcare, 401(k) savings plan, company holidays, paid time off, parental leave, and an employee assistance program.
• Work guided by compassion, integrity, accountability, continuous improvement, and inclusive collaboration.
• Incentive and bonus opportunities may be included in the compensation package.