AI Support Engineer

Enterprise teams still spend too much time moving work across emails, portals, spreadsheets, and legacy systems. Work gets stuck in handoffs, exceptions, and follow-ups. It is slow, expensive, and easy to miss.

We are building the post-RPA agentic automation platform for enterprises — where AI agents execute real work across UIs and APIs, with governance built in. We do not stop at alerts or suggestions. We drive the work to completion, write changes back, and leave proof behind.

We move fast, stay close to reality, and build for live operations — not demo environments.

We are hiring an AI Support Engineer to own a critical layer of product support at Duvo.

This is not a traditional support role. We do not need someone who simply replies to tickets and routes issues onward. We need someone who is AI-first by default, technically strong enough to investigate product behavior in depth, and operationally sharp enough to improve how support works as we scale.

You will be the front line for product and support issues, but also an extension of product, engineering, and solutions. You will investigate problems, reproduce them, identify patterns, improve workflows, and use AI aggressively to increase speed, quality, and leverage.

You should naturally default to AI in how you work: triaging requests, structuring context, accelerating root-cause analysis, drafting responses, improving documentation, identifying patterns, and building support automations. That mindset is not optional here. It is how we work across the company.

• Own incoming support and product issues end to end, from first customer signal to resolution.

• Investigate problems directly in the Duvo platform, Intercom, and internal tooling.

• Reproduce issues, isolate likely causes, and provide engineering or product with high-quality technical context.

• Distinguish between user error, workflow configuration issues, platform limitations, and real bugs.

• Work closely with AI Solutions Consultants, Customer Success, Product, and Engineering to drive fast resolution.

• Use AI tools by default to speed up triage, summarize context, structure escalation packages, and improve response quality.

• Build and refine support workflows, macros, internal copilots, knowledge base content, and repeatable processes.

• Spot recurring issue patterns and feed them back into product, documentation, onboarding, and support automation.

• Help customers understand how the product behaves, especially around AI agent execution, exceptions, approvals, and outputs.

• Improve support scalability over time so human attention goes where it matters most.

This role is for someone who
Is AI-first by default
You already use AI as a core layer of how you work. You do not treat it as a novelty or occasional productivity boost. You instinctively reach for AI to structure, accelerate, analyze, and improve your work.
Is technical enough to go deep
You can investigate product issues with rigor. You are comfortable navigating systems, reproducing edge cases, understanding workflows, reading structured data, and giving engineering useful signal instead of vague symptom reporting.
Thinks like an operator
You care about whether the work actually gets done. You follow through, close loops, and push toward resolution rather than just updating status.
Communicates clearly under pressure
You can explain technical issues simply, calmly, and accurately — both internally and externally.
Improves systems, not just tickets
You do not want to solve the same problem ten times. You look for patterns, automate where possible, and strengthen the support machine over time.
Works independently
You are reliable, responsive, and self-directed. You do not wait to be told where the friction is.

Must-haves
Fluent Czech and English, written and spoken.
Strong written communication in both languages.
Experience in enterprise SaaS, technical support, product support, solutions support, or a similar environment.

• Clear evidence of an AI-first working style — you already use AI tools as a default part of execution, analysis, and communication.

• Strong troubleshooting skills and the ability to investigate issues with precision.

• Ability to reproduce issues and turn ambiguous customer reports into structured technical context.

• High ownership, reliability, and sound judgment.

• Comfort working across support, product, and customer-facing teams.

• Strong attention to detail and a bias toward action.

• Comfort in ambiguity and in fast-changing product environments.

Strong pluses

• Experience supporting AI products, automation platforms, workflow tools, or enterprise software.

• Experience with Intercom or a similar support platform.

• Ability to reason about AI agent behavior, workflow logic, guardrails, approvals, and exceptions.

• Experience creating support automations, macros, internal copilots, or knowledge workflows.

• Familiarity with APIs, structured payloads, logs, SQL, JSON, or basic scripting for investigation purposes.

• Experience building runbooks, escalation frameworks, and internal knowledge bases from scratch.

• Experience working closely with product, engineering, or implementation / solutions teams.

• Strong intuition for what should be automated, what should be productized, and what still needs a human.

How we work
Customer-obsessed
We solve real problems, not hypothetical ones.
AI-first leverage
We use AI by default to move faster and focus human time where it matters most.
Iterative by default
We ship small, learn fast, and improve constantly.
Direct feedback
We say what matters early and clearly so we can keep shipping.
High ownership
If something important is slipping, we do not step around it.

What we offer

• A sharp, motivated team with high standards and low ego.

• The chance to shape how support works at an AI-native company from an early stage.

• Real impact across product, customer experience, and internal operations.

• Competitive compensation and equity.

• The option to trade compensation for equity.

• A front-row seat to building and scaling agentic automation in production.

How we hire
In-person interview (Prague)
We will go through your past work, how you troubleshoot, how technical you are in practice, and how you use AI in your day-to-day work.

Practical exercise / trial day
You will work through realistic support and product scenarios, show how you investigate issues, structure information, and use AI to increase quality and speed.