Head of AI Ops

Coverflex; United States; Remote; USD 90,000 - 112,000; Full time

Job summary

Coverflex is seeking a Head of AI Ops to lead a small central team while staying hands-on, reporting to COO Rui Carvalho. This remote Europe-only role drives AI governance, investments, and cross-functional collaboration to ship impactful automations.

You will own the AI investment case, build reusable AI components, and collaborate with Engineering, Security and Legal. This role requires hands-on tooling and strong exec-facing communication.

Qualifications

• Led company-wide AI or automation initiatives.
• Built AI tools and agents used by teams.
• Managed a budget/investment case with evidence.
• Set cross-department priorities and gained buy-in.
• Knowledge of AI governance, data handling and risk.

Responsibilities

• Own AI/Ops strategy and governance across the org.
• Lead a small team; collaborate with departments.
• Define KPI-driven measurement of AI spend and impact.
• Ensure reusable components and pattern-based work.
• Produce an investment case and report to executives.

Skills

AI leadership across org

Hands-on AI tooling

Budget ownership & governance

Cross-department prioritization

AI governance & risk management

Remote-first work experience

Tools

Claude (Projects, Skills, Plugins)

Notion AI agents

n8n / Make

MCP connectors

SQL

Claude Analytics

Datadog

TypeScript

Python

Job description

Coverflex

Work changed. Pay didn’t.

Coverflex exists to make compensation work for everyone.
Pay is still rigid, fragmented, and hard to feel.
We turn compensation into choice — one platform, one card, one app — for benefits, meal allowance, insurance and more.

Our platform is simple for HR and meaningful for employees.
We provide choice, smarter compensation tools and empowerment.

TL;DR (The Essentials)

Role: Head of AI Ops
Seniority Level: Senior / Head of
Type: Leadership of a small central team while staying hands-on
Reports to: Rui Carvalho, COO
Languages: English (main) / Portuguese, Spanish or Italian a plus
Main Tools:
Claude (Projects, Skills, Plugins) and Notion AI agents
n8n / Make or similar orchestration, plus MCP connectors
SQL, Claude Analytics and Datadog for usage, cost and impact measurement
Scripting (TypeScript or Python) helps, because you should be able to build things yourself

Location: Remote (Europe only)

Compensation:

• Base Salary: 80K to 100K gross annually

• Equity: Yes – VSOPs

• Benefits: See below

• Contract Type: Permanent

Your Impact

Coverflex is roughly 300 people and we spend over €70K a month on AI. Support, Finance, Legal, Ops, Insurance, RevOps and People all build their own agents, skills and automations. We have a plugin registry, a shared skill library and more and more automations that real business processes depend on.

The building works, and people everywhere are shipping. What's missing is someone who owns the whole picture: what we spend, what it returns, what is safe, and what one team built that others could reuse.

Today that sits informally with one person, on top of a full product job, and it deserves a lot more attention.

You lead a small team and decide where it goes. Teams keep their own AI work and pull AI Ops in when they need it, so when two teams want the same people at the same time, you choose. AI Ops doesn't approve anyone's work. It joins a team for a few days, a week or more, builds with them, and hands it back when it's solid. It also looks across everything we build with AI, so other teams can reuse what works.

You own the investment case too: what we spend on AI, what it returns, where we waste it and what we stop doing. When management asks about any of it, you're the one who answers, with evidence.

You'll know you're successful when, after 90 days, you've…

1. Built the first honest picture of AI at Coverflex: spend by tool and team, what runs in production, who depends on it and what it returns

2. Set a priority order across departments and held it, including a "not yet" to at least one senior stakeholder, with a reason they accept

3. Got something live in at least three departments that the department itself now runs

4. Made what already exists findable and reusable, so the second team to need something doesn't rebuild it

5. Agreed a written governance line with Engineering, Security and Legal: what needs a guardrail, what needs review, and what teams can do freely

How we'll measure success:

1. Workflows that changed for good across departments (we don't measure adoption rates or licence counts here)

2. Return on AI spend, with evidence: time saved, cost avoided and better quality

3. Reuse: share of new department AI work that starts from an existing pattern instead of from scratch

4. Coverage of business-critical automations that have a named owner, a defined expected behaviour and an alert path

5. Time from "a department asks" to "someone is working with them", because this team can't become a queue

What This Role Is Not

You won't own the customer-facing AI product.

You won't own infrastructure, hosting, SSO or data access.

You won't approve other teams' work.

You won't only train people.

You won't only set strategy.

Reality Check - What Makes This Role Hard

No department reports to you.

You inherit what's already there.

Requests will outnumber the team from day one.

People watch the spend.

High usage doesn't mean impact.

Each person in your team knows their part better than you.

AI Ops is new.

You

Must-haves (evidence, not years)

You've led AI or automation adoption across a whole company, beyond one team, and can show what changed because of it

You build with AI tools yourself (agents, skills, prompts, orchestration platforms), and other people use what you built

You've owned a budget or an investment case and defended it to executives with evidence

You've set priorities across departments that don't report to you, and made them stick

You know AI governance and risk well enough to draw the line and hold it: data handling, access, vendor review and audit trails

You measure: a baseline before you change something, and proof afterwards

You've worked in fast scale-ups and remote-first teams, with a lot of autonomy

Nice-to-have

Line management of a small, senior, mixed-discipline team

Background in solutions engineering, forward-deployed engineering, internal tooling, revenue/business operations or consulting

Familiarity with the EU AI Act in an employment and financial-services context

Experience in fintech or a regulated environment

Your DNA

Curious about how other people's work gets done, more than about models. Fine being the person who knows least about a domain, and asking the obvious question anyway. Doesn't trust a number that only looks good. Says "we're not doing that" early, before it rots in a backlog. Likes building, including the safety net. Can tell real risk from theoretical risk, and doesn't add process for its own sake.

Who will probably find this frustrating…

Someone who wants a big team and a mandate to enforce. Someone who wants to build new AI systems from scratch, which is closer to what AI Product does. Anyone who needs a stable backlog, a fixed scope or a clean org chart. Anyone whose first move in a governance conversation is to add a form.

Manager & Team

Meet Your Manager

Hiring Manager: Rui Carvalho, COO

Location: Portugal

LinkedIn Profile: https://www.linkedin.com/in/ruigouveiacarvalho/

Profile Snapshot:

Energy: Co-founder and operator. Starts scrappy and validates fast.
Communication: Informal and to the point. Shares ideas while they're still exploratory, and makes sure the people closest to a change hear it first.
Feedback Style: Direct and early. You'll hear it as soon as something isn't aligned or isn't moving, and he'll ask for yours.

How to work with me - in the Manager's own words:

"I'm happy to jump in when you need me, but ideally I don't have to. For that to work, I need transparency on what you're doing and why, and to be aligned before things go out. When we start something we believe will have impact, I stay close at the beginning so we can decide quickly on the risk of launching and move ahead. I care most about clear ownership and hitting what we set out to do. I want to know the impact and make sure we're going after what matters. I also use these tools myself, so you can go into the details with me."

Your Team

You'll set the priorities for:

• Francisco Roza, on the business side: builds and improves agents, and knows how the areas work

• An AI Automation Engineer (open role, separate posting), who goes deep with one team at a time: breaks the problem down, sets up the process and builds it

• Fábio Domingues, on the technical side: looks at how we structure the infrastructure, and is the bridge to Engineering

Key Stakeholders:

• Rui Carvalho, COO, your manager and the executive sponsor of AI Ops

• Martinho Aragão, Head of Product, who runs AI Ops together with Rui until you join and then hands it over

• João Caxaria, Head of AI Engineering in AI Product, which builds CoverflexAI and works in tandem with AI Ops

• Bruno Oliveira, VP Engineering, and the DevX team

• Department leaders across every function

Access & Belonging (Equal Opportunity)

We hire for impact and potential, not pedigree.

We welcome applications from people with non-linear careers, career breaks, caregiving gaps, and those changing fields.

No discrimination on the basis of age, disability, gender identity/expression, marital or family status, pregnancy, neurodivergence, race/ethnicity, religion/belief, sexual orientation, or any other protected ground.

Assessment fairness:

We anchor on evidence of outcomes (what you shipped, moved, or influenced).

We actively de-bias by using structured rubrics, multiple assessors, and blind screening most of the time (we won't know your name, gender, or personal info until the interview stage).

Application Clarity

No cover letter required.

Apply with your LinkedIn or upload your CV.

You may be asked a few short, relevant questions.

Total candidate time investment: ~9 hours end-to-end, including ~4 hours on the case.

Hiring Stages (What to Expect, Why & How Long)

Depending on holidays, we might run some stages in a different order.

1. CV / LinkedIn Screen — Signal check vs must-haves
You'll hear from us within 7 business days.

2. Hiring Manager Interview (COO) - Mandate, judgement and how you operate without authority • 45–60 min

3. Behavioural Interview - With People • 30–45 min

4. Stakeholder Conversation - With two or three of the people you'd work with: AI Product, Engineering and a department lead • 45–60 min
This role only works through people who don't report to you, so they get a say. It's a two-way conversation: they're judging whether they'd pull you in, and you're finding out what you'd be walking into.

5. Case / Work Sample - Your 90-day AI strategy for Coverflex • about four hours to prepare, then 90 min with three of us

6. Final Conversation (CEO / C-Level) — Values, strategy and growth • 30–45 min

Speed & Communication

• Decision: within 4 weeks of your application.

• Updates: weekly if the process runs longer.

• Scheduling: interviews between 9:00 and 18:00 CET (flexible across Europe).

• Feedback: from the Case stage onwards, you'll always receive written or verbal feedback - what went well, and what to strengthen next time.