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The Smarter Way to Work.
AI Operations Engineer – Internal Agents, Workflow Automation
Location
United States
Posted
102 days ago
Salary
0
Seniority
Senior
Job Description
AI Operations Engineer – Internal Agents, Workflow Automation
M-Files
• Discover & shape high-value AI opportunities (internal process focus) • Partner with functional leaders to identify workflows where AI can remove friction, reduce cycle time, improve accuracy, or strengthen compliance. • Map the current state process, identify bottlenecks and failure modes, and re-design the process to be automation-ready (clarify inputs/outputs, decision points, data sources, controls, and ownership). • Define success metrics (time saved, error reduction, throughput, adoption, auditability) and translate business goals into a build plan. • Build internal AI agents and automation tools (end-to-end ownership) • Design and implement internal agents using modern LLM patterns (tool use/function calling, retrieval-augmented generation where needed, structured outputs, and human-in-the-loop checkpoints). • Build whole-product solutions: lightweight UX, service/API layer, integrations, data access, and automation triggers—appropriate to the use case. • Use AI-assisted development techniques to speed delivery while sustaining maintainability and readability. • Operate, maintain, and scale (production mindset) • Own reliability: monitoring, alerting, logging, incident response, and continuous improvements. • Establish repeatable patterns for onboarding new workflows and scaling existing ones (templates, shared components, evaluation harnesses, documentation). • Create and maintain runbooks and lightweight training so internal teams can adopt solutions confidently. • Risk, control, oversight, security & compliance by design • Implement appropriate guardrails: data minimization, access controls, secrets management, safe prompt/tooling patterns, output validation, and traceability. • Ensure solutions meet internal security and compliance expectations (including audit readiness, change management discipline, and clear ownership). • Maintain clear documentation of how systems work, what data they touch, and how risks are mitigated. • Cross-functional coordination • Coordinate across IT/Security, Legal/Privacy, and functional SMEs to get solutions approved and adopted. • Communicate progress with crisp updates; manage tradeoffs between speed and rigor. • Outcomes to be achieved • A portfolio of high-impact internal AI agents deployed into real workflows (not demos), with measurable business outcomes. • A scalable operating model for internal AI: reusable components, clear governance, and a predictable path from idea → production. • Reduced process friction through AI + process redesign, not AI bolted onto broken workflows. • High trust in outputs through appropriate controls, auditability, and operational reliability. • Working style / What success looks like here • You are low ego, high output: you can operate independently, but you collaborate naturally and bring others along. • You can move fast without being reckless: you know where to be scrappy and where to add rigor. • You care about outcomes: automation only matters if it changes how people work.
Job Requirements
- Demonstrated ability to build and maintain end-to-end software (design → build → deploy → operate), with strong engineering fundamentals.
- Proficiency in at least one modern programming language (e.g., Python, TypeScript, C#, Node.js) and comfort learning what’s needed.
- Practical experience integrating systems via APIs, authentication, and structured data formats.
- Strong ability to work with non-technical stakeholders: translate ambiguous problems into clear specs, iterate quickly, and drive adoption.
- Experience building cloud-based services and the surrounding engineering hygiene (CI/CD, source control, test automation, and operational monitoring).
- Comfort with secure and scalable platform concepts (networking, identity, secrets, infrastructure automation).
- Experience or strong interest in AI-assisted development as part of daily engineering practice.
- Hands-on experience building LLM-powered tools/agents (prompting, tool use, retrieval where appropriate, and evaluation/quality approaches).
- Ability to design safe and predictable AI systems (validation, fallbacks, human-in-the-loop, and clear failure handling).
- Familiarity with enterprise security/compliance expectations (access controls, audit trails, change management, data governance).
- Experience modernizing processes (Lean/ops mindset) and designing systems that align to how teams actually work.
- Experience building internal tools that drive adoption across multiple functions.
Benefits
- As remote enabled company our employees enjoy the flexibility to establish their own life/work balance
- Matching 401K Plan (25% of employee's contribution up to the IRS max)
- Health insurance (PPO and HDHP/HSA plans offered)
- Dental insurance
- Vision insurance
- Life insurance (1x employee salary)
- Short-term disability (employer paid)
- Long-term disability (employer paid)
- Flexible Spending Plan (medical and dependent)
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