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AI Engineer

Summary

AI Engineer at WebPros operationalizes and optimizes Large Language Model (LLM) solutions that power products, working on prompt engineering, agentic workflows, safety guardrails, and observability. Core technologies include LLMs, AI coding agents (like Claude Code), and various AI frameworks.

AI Engineer

Department: Engineering – Data & AI

Employment type: Full-time

Location: EU timezone

About WebPros

WebPros is committed to empowering businesses worldwide through cutting-edge solutions in web hosting, billing automation, infrastructure, server management, and online marketing. Since our founding in 2017, we’ve rapidly grown into a global leader, expanding our robust portfolio to include industry-defining brands such as cPanel & WHM, Plesk, WHMCS, SolusVM, XOVI, SocialBee, Sitejet and Comet Backup.

Today, we power 85 million+ websites across 900,000+ servers worldwide, backed by a 650+ strong team of dedicated professionals spanning multiple continents. At WebPros, we embrace a fully remote, borderless workplace with a focus on flexibility, autonomy, and work-life balance. Whether you prefer working from a bustling city hub or a quiet home office, we enable our teams to thrive from anywhere while staying deeply connected through our strong collaborative culture.

Your Role

Join our global Data & AI team at WebPros, where you will operationalise and optimise Large Language Model (LLM) solutions that power our products. You will work across product and engineering teams to design and evaluate prompts and agentic workflows, put safety guardrails in place, and keep our generative AI systems observable, traceable and cost-efficient.

This is a hands-on, technical role with a high degree of autonomy. We are looking for someone who can take an abstract goal, break it down into concrete steps, and drive it to completion.

How you’ll work (AI-native)

We work AI-native, and we expect the same from this role:

You develop and explore code primarily through AI coding agents (e.g. Claude Code), including navigating and changing large, unfamiliar codebases.

You practise agentic engineering: a structured engineering process where intent is the source of truth, and where you rigorously review what the agents produce to confirm it is correct and well-designed.

You are comfortable with the common building blocks of harness engineering (e.g. MCP, Skills and Plugins, subagents, spec-driven development frameworks such as Spec Kit) and know when to reach for each.

We don’t require extensive prior experience in software development, but you need to comfortably reach correct, well-reasoned results with AI agents. Therefore, experience programming in popular scripting languages (e.g. TypeScript, Python) is required.

Key Responsibilities

As an AI Engineer, your key responsibilities will include:

Designing, testing and optimising agentic design patterns using techniques such as zero-shot, few-shot, chain-of-thought, ReAct, and others.

Designing and comparing agentic architectures (single-agent loops, multi-agent systems, prompt-template pipelines) and choosing the right one for the task on cost, latency and quality.

Evaluating and recommending models, both small and large, across closed-source, and open-weights options, and designing model routing and selection to balance quality, cost and latency.

Building and running strong evaluation pipelines, offline and online: assembling datasets, defining metrics (similarity scores, LLM-as-a-judge, cost, latency, quality) and tracking generation quality over time.

Implementing guardrails through input/output validation, including prompt-injection prevention, toxicity filtering and hallucination detection.

Integrating our systems with LLM observability platforms to monitor latency, token usage, error rates and cost, and using that visibility to inform guardrails and optimisation.

Integrating LLM workflows into our products and services.

Supporting AI risk assessments and compliance efforts.

Your Qualifications

Must-Haves

To be successful in this role, you should bring:

An AI-native working style: fluency with AI coding agents (e.g. Claude Code) for building and exploring code, and the judgement to assess what they produce.

Autonomy: a track record of taking an abstract goal, scoping it yourself and delivering it with little supervision.

Hands-on prompt engineering and optimisation, including agentic prompting (experience with an optimisation framework such as DSPy is welcome).

Practical experience with testing, evaluating, and red teaming LLM applications: designing evals, building datasets, defining testing strategies, and comparing and selecting models (frontier, and open-weights), with tools like Promptfoo.

Experience with LLM observability, monitoring, logging and traceability (e.g. Langfuse, MLflow, etc.).

Familiarity with AI guardrailing techniques (e.g. Guardrails AI, LLM Guard, ...).

Comfort working with LLM APIs and SDKs in code (e.g. Anthropic Claude, OpenRouter, Pydantic AI, LangChain, Vercel AI SDK, etc.).

An understanding of AI governance and risk management practices.

Strong English (C1 level), with the ability to explain complex AI concepts clearly to both technical and non-technical audiences.

Nice-to-Haves

Experience with open-weights models and fine-tuning, ideally building a reusable training pipeline (data, pipeline, model) that can be pointed at new tasks rather than a one-off.

Experience with text-generation use cases, which is where most of our work sits.

Experience setting up and working with MCP and A2A.

Your Impact In The First 120 Days

30 Days – Learn & Integrate

Get up to speed on WebPros’ product portfolio, data infrastructure and existing GenAI use cases across teams.

Set up your AI-native workflow (Claude Code, MCP servers, agentic tooling) and start exploring our codebases with AI coding agents.

Meet product and engineering stakeholders across brands to understand where LLM workflows are already in play.

Review current prompt designs, evaluation practices (if any) and observability gaps.

60 Days – Contribute & Collaborate

Ship your first prompt or agentic workflow improvement, or evaluation pipeline, for an existing LLM use case.

Stand up baseline observability (latency, token usage, cost, error rate) for at least one production LLM workflow.

Start red-teaming or guardrail work on a live use case (prompt-injection, hallucination, toxicity checks).

Collaborate with product and engineering teams to scope the next LLM integration.

90 Days – Take Ownership

Own the evaluation strategy (offline and online) for a core LLM workflow, including dataset assembly and quality metrics.

Recommend a model routing/selection approach balancing cost, latency and quality for at least one product surface.

Present findings from red-teaming or guardrail testing, with concrete remediation steps.

120 Days – Drive Growth

Run end-to-end agentic architecture decisions for a new LLM-powered feature, from design to guardrails to observability.

Support AI risk assessment and compliance work with a clear point of view on governance gaps.

Be a go-to resource for prompt engineering and AI-native development practices across product and engineering teams.

You Might Thrive Here If You, You Might Struggle Here If You

You’ll Thrive Here If…

You default to picking up an AI coding agent to explore and build, rather than writing everything by hand.

You’re comfortable taking an abstract goal and scoping your own path to get there, with little day-to-day supervision.

You enjoy the unglamorous half of AI work – evals, guardrails, observability – not just prompt design.

You like working directly with product and engineering teams rather than in an AI research silo.

You Might Struggle Here If…

You expect a fully-scoped backlog of tickets rather than an open-ended mandate.

You’re not yet comfortable reviewing and correcting AI-agent-generated code.

You prefer working with one frontier model in isolation over comparing and routing across multiple models.

You’d rather avoid the governance, risk and compliance conversations that come with shipping LLMs in production.

How We Work

Team & Workflow: Remote, asynchronous.

Collaboration & Ownership: Self-managed work with a strong emphasis on being autonomous and proactive with good time management.

Our Culture

WebPros is built on diversity, not just in principle but by design. We’ve grown through acquiring industry-leading brands, bringing together teams from 42+ nationalities, 20+ countries, and 10+ brands. Instead of enforcing a one-size-fits-all culture, we embrace unique perspectives, different working styles, and localized expertise to drive global innovation.

We are a fully remote, async-friendly company where transparency, open communication, and collaborative problem-solving define how we work. Whether you thrive in the fast pace of a startup or the stability of an established product, WebPros offers a dynamic, evolving career journey that you can shape based on your strengths.

We are committed to fostering an inclusive, equitable workplace where every team member feels valued, heard, and supported because our diversity is our strength.

Compensation & Benefits

We believe benefits go beyond just perks. At WebPros, we invest in your growth, flexibility, and well-being, so you can do your best work and build a meaningful career. While we strive to provide equal global benefits for all team members, some may vary by location, and we’ll clarify the details with you during the interview process.

Competitive salary

Remote-first flexibility: Work from anywhere in Europe (or hybrid in available offices).

Development Budget: Annual personal growth allowance.

Learning Support: Udemy subscription & peer learning.

Public Transport & Meal Vouchers: Location-dependent benefits.

Paid Time Off: 20+ days of annual leave.

Team Culture: Regular team and on-site company events.

Your Hiring Experience

Hi, I am Zornitsa your Talent Partner at WebPros. I’ll guide you through the interview process, ensuring a clear, transparent, and meaningful experience.

Interview Process

Hiring Manager Interview (45 min): Discussion with Oleh Tsyhulov to assess team fit, self-reliance, technical alignment, and problem-solving skills.

Technical & Culture Interview (60 min): Deep dive into technical expertise, problem-solving, adaptability.

Our Commitment to a Diverse & Inclusive Culture

At WebPros, we want every team member to feel excited to bring their full, authentic self to work. Our strength lies in the diversity of our people, with different backgrounds, perspectives, and experiences driving innovation and making us stronger together.

We are committed to ensuring equitable opportunities, pay, and support for all employees, regardless of identity, background, or circumstances. We foster a culture of belonging, respect, and psychological safety, where everyone feels valued, heard, and empowered to contribute meaningfully and grow.

Discrimination of any kind, including sexism, racism, xenophobia, homophobia, transphobia, ableism, and ageism, has no place here. By embracing differences and championing inclusivity, we create an environment where everyone can thrive.

We are looking forward to your application!

#LI-DNI

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