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AI Operations Engineer (Internal Agents & Workflow Automation) (Remote, US)

APPLICATION WINDOW: We encourage you to apply if interested. We will review applications on a rolling basis and keep candidates informed on next steps.

We recognize that job searching can sometimes feel uncertain. As we engage with candidates and continue to evaluate our needs, this role may evolve to ensure strong alignment between the opportunity, the market, and long-term success.

We are committed to a thoughtful and transparent process and will keep candidates informed along the way. Thank you for considering M-Files as your next career move.

Who We Are

M-Files is redefining how work gets done. Our context-first document management system offers purpose-built business use cases—spanning universal and industry-specific workflows—to enable secure collaboration, automate processes, and ensure governance.

Unlike traditional systems, M-Files organizes content around the context of your business, connecting documents to related people, projects, and transactions. With our unique metadata-driven architecture, organizations can model content in line with their business processes, unify information across silos, and apply AI at scale. The result is greater productivity, reduced risk, and smarter, faster decisions for over 6,000 customers in 100+ countries.

At M-Files, our Guiding Principles unite us across diverse cultures and personalities:

1.       Make It Happen – We set bold goals, take ownership, learn from mistakes, and relentlessly pursue results.

2.       Help Others – We lead with kindness, assume good intentions, hold one another accountable, and celebrate wins together.

3.       Love Customers – We put customers and partners at the heart of everything, delivering value with respect, fairness, and speed.

To learn more about us we encourage you to visit our company page.

To learn more about how we became a Certified Great Place to Work visit, Working at M-Files | Great Place to Work.

Summary of the Role

M-Files is building a company-wide capability to operationalize AI—turning promising LLM prototypes into secure, reliable, maintainable internal tools that materially improve how teams work. This role sits in Strategic Operations and functions as a hands-on builder: you will partner with business leaders to identify high-value workflows that can be accelerated with AI, help reshape the underlying processes, and then build, deploy, and run the AI-enabled solutions end-to-end.

This is not a traditional product software engineer role. Instead, it is an execution-oriented engineering role embedded in the business: you’ll move quickly from problem definition to production, while applying the right risk controls, oversight, security, and compliance expectations required for internal systems at scale.

You will leverage AI-assisted development tools as part of your daily workflow to accelerate delivery while maintaining quality.

What You Will Be Doing / Responsibilities and Duties

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, mantain, 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.

Qualifications

  • 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.

Technical foundations we value (examples)

  • 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.

 

LLMs/agent capabilities (expected for this role)  

  • 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).

 

Preferred

  • 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.

 

Participation in our Recruitment Process: To Be Determined. Typical interview processes including initial screening w/ a Recruiter, meeting with Hiring Manager (SVP, Strategic Operations & Corporate Development), and other internal team members the role may closely interact with.

*Estimated total candidate time investment: Approx. 3hrs

Why M-Files?

M-Files is a global company with Finnish roots, built around a product we are proud of.

You’ll have the opportunity to contribute to our continued growth while developing your own expertise in a collaborative, supportive environment.

Our guiding principles, Make It Happen, Help Others, Love Customers, are reflected in how we work every day, with transparency and strong team spirit at the core of our culture.

What We Offer:

  • 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)
M-Files Glassdoor Company Review
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CEO of M-Files
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Antti Nivala
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Average salary estimate

$170000 / YEARLY (est.)
min
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$140000K
$200000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

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Full-time, remote
DATE POSTED
April 8, 2026
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