AI Engineer - Agentic Plattform (m/f/x)

ID: 9175

Type: Full-time

Category: Others

Company Name: Cloudflight

Location: Romania, Austria, Germany

Salary: 54 - 54K yearly

Job Description

At Cloudflight, we’re committed to making a digital difference. It’s a difference that impacts businesses and society alike and one that’s fueled by our passion for technology and our dedication to sparking the brightest ideas in ourselves and others.

Role Overview

We are looking for a Platform AI Engineer who will design, build, and scale our AI platform capabilities, enabling seamless model development, deployment, monitoring, and lifecycle management across the organization. You will bring together engineering excellence, MLOps best practices, and a product mindset to turn AI into a reliable, secure, and operational capability.

Responsibilities

Design and operate scalable AI/ML platforms, including training, inference, pipelines, and feature stores

Automate MLOps workflows (deployment, orchestration, CI/CD, monitoring, observability)

Optimize GPU/accelerated environments for high-performance model workloads

Build reusable services, APIs, and tooling to boost engineering and data science productivity

Ensure security, compliance, governance, and Responsible AI across the full model lifecycle

Evaluate and adopt emerging AI technologies to continuously improve the platform

Collaborate with cross-functional teams to deliver reliable, scalable AI products

Improve cost efficiency and performance of training, experimentation, and inference

Perform LLM pre-training, fine-tuning, and evaluation to ensure quality and reliability

Design strong prompts, guardrails, and safety filters for secure LLM operation

Develop and maintain RAG capabilities for enterprise knowledge access

Build AI agents augmented with tools and internal system integrations

Requirements

5+ years of experience in Machine Learning Engineering, AI Platform Engineering, or MLOps

Hands-on expertise with AI/ML tooling and orchestration (e.g., Databricks, Azure ML, MLflow, VertexAI, Kubeflow, Airflow)

Strong software engineering background in Python (and ideally Java/Go); experience building reliable services/APIs

Deep knowledge of cloud native architectures (Azure / AWS / GCP), including containerisation (Docker, Kubernetes) and Infrastructure-as-Code

Experience with GPU/accelerated infrastructure, model optimization, and high-performance workloads

Familiarity with monitoring and managing production models (drift detection, lineage, model registry, A/B testing)

Solid understanding of data architecture + integration with data platforms

Strong communication skills, able to partner with cross-functional teams and translate platform needs into technical solutions

Fluency in English (additional regional languages a plus)

Why this role matters

You will build the foundation that enables scalable, secure, and production-ready AI — accelerating innovation and ensuring our teams can move from experimentation to business impact faster than ever.

Austria: The law stipulates that the minimum wage must be specified in job postings. The minimum salary is 53.802 euros/year in the collective agreement. Adequate to your skills, we are willing to pay much more.

We are an equal opportunity employer. We strive to create an inclusive environment where everyone can thrive regardless of their background and circumstances. All applicants receive equal opportunity regardless of age, gender identity or expression, language, disability, ethnicity, national origin, religion, or sexual orientation.

We will go through your application and come back with feedback.

Any questions? Contact us at jobs@cloudflight.io

Company Information

Company Name: Cloudflight

Company Website: https://cloudflight.io

Company Address: Munich, Bavaria, Germany

Cloudflight is a European digital engineering firm that provides end-to-end software and systems engineering services focused on cloud-native architectures, data and artificial intelligence, and product-driven digital transformation. The company positions itself as a technology partner for organizations that need to modernize IT landscapes, build new digital products, scale data and analytics capabilities, and operationalize machine learning. Cloudflight combines multidisciplinary engineering teams—software developers, data engineers, machine learning engineers, DevOps and platform engineers, UX designers, QA and security specialists—to deliver solutions that range from advisory and proof-of-concept work through implementation, deployment, and long-term managed operations. Core business activities Cloudflight’s core activities center on designing, building, and running digital systems and platforms. Key areas of work include cloud transformation and platform engineering (including cloud-native application development, microservices, containerization, and infrastructure-as-code); data engineering and analytics (data pipelines, data warehouses/lakes, real-time streaming and batch processing); applied artificial intelligence and machine learning (model development, MLOps, model deployment and lifecycle management); and integration of enterprise systems and APIs. The company also routinely provides product engineering and software development for customer-facing applications—mobile apps, web front ends, and backend services—bringing together human-centered design and scalable engineering practices. Main products and services Cloudflight delivers a mix of consulting-led engagements, project delivery, and managed services. Typical service offerings described by the company include: strategy and discovery (digital strategy, architecture reviews, feasibility studies, and prototyping); engineering services (full-stack development, backend and middleware, IoT and embedded systems, real-time systems); data & AI services (data strategy, data platform implementation, analytics, ML model development and operationalization, MLOps pipelines); cloud services (cloud adoption, migration, cost optimization, platform engineering and cloud-native operations); and platform and product engineering (building and operating platforms for e-commerce, industry-specific solutions, and digital ecosystems). In addition, Cloudflight provides quality assurance and security services—test automation, performance engineering, and security assessments—to ensure solutions meet enterprise requirements. Delivery approach and capabilities The company emphasizes an engineering-first, product-oriented delivery model with cross-functional teams that integrate domain expertise, design thinking, and agile product management. Projects frequently start with discovery and prototyping to validate technical approaches and business value, followed by iterative development cycles to build minimum viable products and scale them into production-grade systems. Cloudflight highlights capabilities in modern DevOps and platform practices—CI/CD, infrastructure-as-code, observability, and automated testing—to accelerate delivery and make systems maintainable. For data and AI initiatives, the firm focuses on end-to-end data architecture, from ingestion and storage to feature engineering, model training, deployment, and monitoring, often implementing MLOps practices to ensure reproducible and reliable model operations. Industries and use cases Cloudflight works with organizations across multiple industries where cloud, data, and AI can drive operational improvements and new digital services. Commonly addressed industry use cases include predictive maintenance and digital twins for manufacturing and industrial companies; smart products and connected services for automotive and IoT-focused businesses; customer-facing digital platforms for finance, insurance, and retail; analytics, regulatory and reporting solutions for financial services; and data-driven services for utilities and energy companies. The company also undertakes public sector and healthcare projects that require secure, compliant solutions. Use cases frequently emphasize improved time-to-market for digital products, cost reduction through cloud optimization and automation, and new revenue streams enabled by data-driven services. Engagement models and client relationships Cloudflight offers flexible engagement models including time-and-materials teams, fixed-scope projects, outcome-based engagements, and longer-term managed services. The company typically embeds multi-disciplinary teams with client organizations or operates as an external product engineering partner depending on client preference and the nature of the engagement. Emphasis is placed on knowledge transfer and building internal capabilities where clients wish to operate systems themselves; alternatively, Cloudflight can provide ongoing operations and managed platform services. Technology focus and tools The company’s technology focus is on modern cloud platforms, containerization, microservices, orchestration, and data platforms that support both batch and streaming workloads. For machine learning and AI work the firm implements reproducible data pipelines, model training and validation processes, and model deployment approaches that are compatible with enterprise operations and governance requirements. Implementation stacks and tools are chosen to meet client constraints and typically include open-source and cloud-provider technologies to balance extensibility and vendor support. Security, compliance, and observability are integrated into designs to meet enterprise requirements and maintainability goals. Market positioning and value proposition Cloudflight markets itself as a partner for enterprises looking to accelerate their digital transformation by combining strong engineering capabilities with domain-driven product development. The company’s value proposition centers on delivering production-ready software and data products quickly while ensuring those systems are scalable, secure, and operable. By applying modern engineering practices—agile product management, continuous delivery, and DevOps—Cloudflight aims to reduce time to value, de-risk cloud and AI initiatives, and help clients move from experimentation to production at scale. Summary In summary, Cloudflight is a technology-focused digital engineering company that provides cloud-native software development, data engineering, and applied AI services, along with platform engineering and managed operations. It supports clients across a range of industries with end-to-end delivery—from strategic assessments and prototyping to implementation and ongoing operations—leveraging modern cloud, data, and DevOps practices to build and run resilient, scalable digital products and platforms.

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