Job description
About Qualifyze:
Founded in ****, Qualifyze is a leading company in supply chain compliance management in the Life Sciences industry, trusted by over 1,500 pharmaceutical and healthcare companies globally. Our digital suite of solutions connects manufacturers, suppliers, and a general network of more than 250 auditors and quality experts.
With a track record of over 4,500 audits across 85+ countries and the largest and most accurate supplier network and data analytics
tools, Qualifyze stands as the all-in-one partner for quality compliance and supply chain risk mitigation in the Life Sciences sector.
Job requirements
Role Overview:
As an
AI Agents Engineer,
you sit at the
intersection of business, data, and technology,
and you use that vantage point to scale
how the organization works
. Your mission is to understand our business and its processes deeply, identify where they can be made faster, simpler, and more reliable, and
deliver data-driven, automated, AI-powered solutions
that raise productivity, sharpen decision-making, and drive operational excellence across the company.
This is a
business-first, deeply technical role
. You combine a genuine understanding of
how the business runs with strong engineering skills
, including
data engineering,
programming
, and
enough DevOps fluency
to prepare your solutions for clean, standardized handover to production.
This role is
integrated in the BI team, which sits within the Finance department.
Main responsibilities:
The team member shall perform the present tasks inherent to such position, including, but not limited to, the following:
Partner with business teams




to develop a deep understanding of their processes and to identify and scope high-impact transformation opportunities through AI and automation.
Define the
business problem, success metrics, feasibility, risks, and ROI.
Map, document, and analyze the current processes, systems, and data flows
across the existing tool landscape. Challenge existing processes and assumptions, identify bottlenecks, and propose new workflows and tooling that enable scalability and efficiency.
Design and deliver new solutions end-to-end, from proof of concept to production.
Develop automation and AI-based systems such as
intelligent routing, workflow orchestration, and AI agents running in production
, integrated with internal platforms via
APIs and webhooks
.
Prepare and package solutions according to the standards of the DevOps team
so they can be deployed and operated in a plug-and-play manner. This does not mean acting as a DevOps engineer, but having a
solid conceptual understanding of containerization (Docker), orchestration (Kubernetes)
, and modern deployment practices, so that what you build fits seamlessly into our operational standards.
Establish
quality, performance, and safety monitoring
for all solutions, including the
LLM-powered agents running in production.
Work closely with the AI team to ensure compliant usage of Agents. Create documentation, runbooks, and handovers to ensure sustainable operations.




Design
ingestion and transformation pipelines using dbt,
to support automation, analytics, and decision-making at scale.
Act as a catalyst for continuous improvement by challenging the status quo and driving operational excellence through innovation and simplification.
What are we looking for?
Deep understanding of business processes, with a
strong process-mapping and optimization mindset,
focused on measurable efficiency gains and anticipation of edge cases and failure modes.
Strong programming skills in
Python and/or Java, with strong SQL
, for automation, data transformation, and system integration.
Proven experience building and maintaining
ETL/ELT pipelines using dbt
or similar frameworks.
Hands-on experience executing automations.
Practical experience with LLMs and AI agents,
including building and running
agentic workflows in production,
and a habit of actively keeping up to date with the fast-evolving developments in the field.
Solid conceptual DevOps knowledge,
including
containerization (Docker), orchestration (Kubernetes),
and deployment practices, sufficient to prepare solutions to the standards of a DevOps team for smooth, standardized deployment.
Familiarity with
integrating APIs and webhooks
to automate cross-system workflows.
Experience working with cloud platforms such as
AWS, GCP, or Azure.
Excellent
collaboration, stakeholder communication, and ownership
across technical and business teams, and participates in code/design reviews.
A proactive and self-driven mindset, with a passion for solving complex problems through simple, scalable solutions,
under

📌 Ai Agents Engineer (Laza)
🏢 Qualifyze
📍 Laza