Sales Engineer Undergraduate

We’re looking for a

Solutions Architect / Presales Engineer

with experience in the software industry, ideally having worked in similar roles involving complex data or AI-related platforms.

As a Solutions Architect / Presales Engineer, you’ll play a key role in shaping the future of data management through a

cutting-edge Generative AI Data Fabric Platform

• . You will support incoming business opportunities by translating customer needs into actionable technical solutions using the platform. This technology has a major impact on how companies manage data, analytics, and AI across their organization.

You will engage with stakeholders from large companies — both technical and business decision-makers — as well as with strategic partners. In a fast-paced, dynamic environment, your primary mission will be to

demonstrate the value and fit of the product

within the client’s enterprise

ecosystem.

RESPONSIBILITIES

Collaborate closely with clients and partners to understand their business challenges and data needs. Participate in requirement-gathering sessions and guide toward the best possible solution ( win-win

approach).

Lead the preparation of RFPs, RFIs, and commercial proposals alongside partners or clients.

Estimate team efforts and project costs using internal methodologies.

Coordinate technical requirements with internal teams.

Identify risks early and assess their potential impact.

Design and define solution architectures integrating the platform with other third-party providers or systems.

KEY SKILLS & REQUIREMENTS

Mandatory Requirements :

Previous experience leading presales opportunities or implementing data solutions (e.g., big data, data governance, advanced analytics, or cloud / data migrations).

Strong communication and problem-solving skills : ability to listen actively, ask the right questions, and propose clear, creative solutions.

Strong leadership and negotiation skills with a win-win mindset.

Ability to design and articulate high-level technical solutions for large-scale systems.

Team player with a goal-driven and adaptable mindset.

Ability to deliver demos, workshops, and POCs effectively.

Strong presentation skills for diverse audiences, from C-level executives to technical teams.

Technical Knowledge :

Solid understanding of

software architecture

design patterns

data structures

generative AI

machine learning algorithms

, and

data governance

best practices.

Hands-on knowledge of

Apache Spark

PySpark

MLflow

, and data pipelines.

Familiarity with frameworks for building agentic systems, retrieval-augmented generation (RAG), and related AI tools.

Experience using AI coding assistants (e.g., Windsurf, Cursor, Copilot) to rapidly develop prototypes.

Basic experience with

Kubernetes

concepts (deployments, services, ingresses, namespaces, cluster policies, etc.).

Experience working with Kubernetes clusters in one or more environments (e.g., AKS, EKS, GKE, Minikube, Kind, Openshift, Rancher).

Proficient English

(spoken and written – minimum C1 or equivalent) is essential to work in an international environment.

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