We are currently looking for a Key Account Manager Enterprise Cloud (80–100%) based in Zurich. This role is ideal for a motivated professional who wants to drive the acquisition of new customers and expand the client base for innovative Enterprise Cloud solutions. Flexible mobile working is possible.

Your Role
As a Key Account Manager, you will play a key role in acquiring new customers for Enterprise Cloud solutions and continuously expanding the client base. Your primary workplace will be the office in Zurich, with the possibility of mobile working.

Location: Zurich, Switzerland

Your Responsibilities

• Acquire new clients using an innovative cloud solutions portfolio

• Maintain and expand existing customer relationships

• Prepare and deliver customer presentations

• Create offers and manage tenders together with the Presales team

• Work closely with partners and customers

• Collaborate with the Cloud Engineering team

• Maintain direct client contact throughout all project phases

Your Expertise

• Strong interest in Cloud Native, DevOps, HCI, and Security in private, hybrid, and multi-cloud environments such as AWS and Azure

• Experience in selling enterprise solutions and IT services

• Very good Microsoft Office skills including Word, Excel, and PowerPoint

• Good written and spoken German and English

• Professional manner when interacting with customers and colleagues

• Quick learner with willingness to develop in new areas

Your Personality

• Service-oriented, flexible, and supportive

• Confident personality with high commitment and ownership

• Clear communication, structured and independent work, strong quality standards

• Persistent in solving challenges and enjoys working in an intercultural team

• Reliable and collaborative team player actively contributing to shared success

What We Offer

• Open and transparent culture with a partnership approach

• Ideas and innovative thinking are welcome

• Local decision-making with agility

• Professional and personal development opportunities

• Attractive compensation, social benefits, flexible working conditions, and training programs

About the Company

The company builds an AI-powered workflow intelligence platform that helps organizations prevent revenue loss before it happens.

By analyzing API-enabled metadata from existing business systems, the platform automatically identifies misalignment between teams such as Sales, Customer Success, Legal, Finance, Product, and Operations — before deals stall, renewals fail, or contracts slip.

The solution requires:

• no workflow changes
• no heavy integrations
• rollout in less than two days

The AI continuously learns what successful execution looks like within each organization and alerts teams in real time when dangerous deviations occur.

The founding team has previously built and scaled a B2B platform adopted by hundreds of financial institutions, which was later successfully acquired. Those lessons are now applied to execution, delivery, and scale. The product is supported by senior leaders from large enterprise and SaaS companies across fintech, HR, ERP, healthcare, and enterprise software.

Position Overview

We are looking for a Senior AI Backend Engineer to design, build, and scale the core systems behind a workflow intelligence platform.

The platform connects to customer systems, ingests large volumes of event-based metadata, reconstructs real business workflows, and applies machine learning to:

• discover ideal process paths (“golden paths”)

• detect anomalies

• surface actionable insights

The system processes fragmented signals from multiple business systems (CRM, communication tools, internal platforms) and reconstructs unified workflows using techniques such as embeddings, similarity search, and probabilistic matching.

This is a hands-on senior role for someone equally strong in backend & distributed systems, data-intensive architectures, applied machine learning, experimentation & research, and production-grade reliability.

Core stack: Python, MongoDB, ClickHouse, RabbitMQ
Additional technologies used: C# (.NET Core / ASP.NET Core)

We’re looking for an engineer who deeply understands system architecture, large-scale data processing, and production ML systems, and is comfortable building, training, experimenting with, and deploying ML models into production.

Location: Ukraine or Europe (remote)

What You Will Do

Backend & Systems

• Design and build backend services and APIs using Python (experience with C# / .NET Core is a plus)

• Architect scalable, fault-tolerant, and observable systems for large-scale event ingestion, processing, and analytics

• Build event-driven and asynchronous pipelines using RabbitMQ

• Design data models and storage strategies using MongoDB and ClickHouse

• Work with high-volume metadata streams from multiple external systems

• Own system performance, reliability, and scalability

• Implement observability: logging, metrics, tracing, and alerting

• Troubleshoot production issues, perform root cause analysis, and implement long-term fixes

Data & Machine Learning

• Design and implement end-to-end ML pipelines: ingestion → feature engineering → training → evaluation → deployment

• Train and iterate on ML models for workflow discovery, anomaly detection, and behavioral pattern recognition

• Work with large-scale event streams and metadata pipelines

• Apply techniques such as embeddings, similarity search, probabilistic matching to link fragmented entities (tasks, communications, leads, opportunities) into unified business workflows

• Run experiments, test hypotheses, and evaluate models using offline and online metrics

• Conduct applied research and explore new modeling approaches

• Build batch and near-real-time inference pipelines

• Monitor model performance, drift, and degradation in production

• Implement retraining strategies and model versioning

Required Qualifications

• 6+ years of experience in backend or systems engineering

• Strong hands-on experience with Python

• Experience building data-intensive systems (event ingestion, pipelines, analytics)

• Experience processing large-scale event streams or metadata pipelines

• Practical experience working with machine learning systems in production

Experience with:

• model training

• feature engineering

• experimentation

• model evaluation and monitoring

• Familiarity with techniques such as embeddings, similarity search, or probabilistic matching

• Ability to work with uncertain or fragmented data signals when reconstructing workflows across multiple systems

• Experience with MongoDB, ClickHouse, or similar analytical databases

• Experience with message brokers (RabbitMQ or similar)

Strong understanding of distributed systems concepts, including:

• idempotency

• retries

• backpressure

• eventual consistency

• failure modes

• Excellent analytical and problem-solving skills

• High ownership mindset and ability to take responsibility for end-to-end solutions

Nice to Have

• Experience with C# / .NET Core / ASP.NET Core

• Experience with workflow analytics, process mining, or event-based systems

• Experience with entity linking, similarity search, or graph-like data models

• Familiarity with time-series or behavioral modeling

• Experience with large-scale experimentation platforms

• Understanding of MLOps practices

• Experience with cost optimization for data and ML workloads

• Experience with Kubernetes and cloud infrastructure

If you enjoy working at the intersection of systems, data, and intelligence, this role is a strong fit.

What They Offers

• Senior role owning core backend systems behind an AI/ML product
• Direct collaboration with ML Engineers to bring models into production
• Real-world data engineering challenges with visible impact
• Fast iteration, low bureaucracy, and high trust
• Remote-friendly team with strong engineering standards
• Competitive compensation and growth opportunities as the company scales

Operating Model & Expectations

• LinkedIn profile required and kept up to date (company policy)
• Synchronized team vacations (four times per year)
• Startup constraints during critical periods
• Relocation readiness (Ukraine → Europe or US if legally possible)
• Flexible schedule for cross-time-zone collaboration
• High-performance culture with fast decisions and clear accountability