AI Engineer

Why Join UsAt Cloudfide, we engineer solutions where data truly becomes an accelerator for innovation. We build and evolve large-scale Big Data and cloud-native platforms for global clients, including leaders in retail and the Fortune 500. We process massive, complex datasets, operate fully in the cloud ecosystem, and work with the latest technologies, including AI, ML, MLOps, and modern data architectures.

Our projects have measurable, real‑world impact - from enhancing customer experiences at scale to empowering data-driven decision-making in high‑visibility global organizations. As we continue to grow, you'll have the opportunity to shape solutions, mentor others, drive architecture decisions, and take ownership of strategic initiatives.

Opportunity OverviewAs a Mid AI Engineer at Cloudfide, you will work on a meaningful, production-grade GenAI project for a Fortune 500 client. Your core mission: take a complex, manual, people-driven data publication process and transform it into a codified framework of autonomous agent 'skills' - enabling a downstream agent to execute that process independently and reliably.

You'll be authoring agentic skills, integrating with data catalog and metadata APIs, and working within a Databricks-based ecosystem. This is not a research role and not classic ML - it's applied GenAI engineering at the intersection of automation, data infrastructure, and intelligent systems.

Expect a collaborative, AI-forward environment where thinking outside the box is encouraged and your proactivity is genuinely valued. You'll join a team of passionate engineers who value technical excellence, collaboration, and continuous growth.

Your Responsibilities

Designing and building GenAI agent skills that codify manual, knowledge-based processes into structured, reusable frameworks consumable by autonomous agents.

Authoring agentic skills using markdown-based and programmatic approaches within established GenAI frameworks.

Building and maintaining agentic pipelines using LangChain and/or LangGraph.

Integrating with data catalog and metadata APIs (Unity Catalog, DDAPI, and similar) to enable autonomous data publication workflows.

Working within the Databricks ecosystem - including Unity Catalog and Genie - to support data access, governance, and agent interaction patterns.

Collaborating closely with stakeholders across technical and non-technical disciplines to understand process logic and translate it into agent-ready specifications.

Operating with a high degree of autonomy - scoping work, identifying gaps, and driving delivery without constant hand-holding.

Leveraging AI tools in day-to-day work to continuously improve productivity and output quality.

What We're Looking For2+ years of commercial experience in an AI or software engineering role with a clear GenAI or agentic focus.

Hands-on experience building with LLMs in production or near-production contexts - prompt engineering, agent orchestration, tool use.

Practical experience with agentic frameworks - LangChain and/or LangGraph strongly preferred.

Familiarity with Databricks, including Unity Catalog; exposure to Genie is a plus.

Experience integrating with APIs - metadata APIs, data catalog APIs, or similar.

Comfort working in interdisciplinary environments - able to engage with data engineers, platform teams, and business stakeholders alike.

Strong stakeholder-facing communication skills - able to extract process knowledge from domain experts and translate it into technical specifications.

Self-directed and reliable - able to manage ambiguity, drive work forward, and flag blockers proactively.

Fluent English, able to collaborate effectively across international teams.

What This Role Is Not

This is not a classical ML or data science position. Candidates with a primary background in model training, statistical analysis, or MLOps pipelines - without meaningful GenAI or agentic experience - are unlikely to be a strong fit.

Nice to Have

Experience with data catalog platforms or data publication workflows.

Familiarity with markdown-based skill or prompt authoring frameworks.

Knowledge of data governance concepts and metadata management.

Experience working in large enterprise data ecosystems.

Python proficiency in the context of agentic or LLM-based systems.

Here's why you'll love Cloudfide

Benefits:

MyBenefit platform / Multisport

Enel‑Med private medical care

Professional Growth:

Annual 2,000 PLN development budget

Access to e‑learning platforms

Real opportunities to expand responsibility and lead initiatives - most of our Leads come from internal promotionsAs the company continuously grows, you get real opportunities to expand your responsibilities, explore new areas, and even take ownership of your own initiatives.

Work Environment:

Long-term cooperation: UZ or B2B (we value stable, lasting relationships)

Remote-first, work from anywhere in the world (workation)

Flexible hours & strong focus on work-life balance

Collaboration with top engineers you can truly learn fromFlat structure - every voice counts, and you help shape the company

Culture & Integration:

Company-wide trips (including international ones)

Team integration budgets

• Open communication and supportive, passionate teams
• Equal Opportunities
• CLOUDFIDE is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.