Complexio | Senior DevOps Engineer

Complexio
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist | Digital Services

Data Scientist – 11323SR4

Machine Learning Engineer

Lead Machine Learning Engineer

Informatics Data Science Manager

Data Scientist

Complexio is Foundational AI works to automate business activities by ingesting whole company data – both structured and unstructured – and making sense of it. Using proprietary models and algorithms Complexio forms a deep understanding of how humans are interacting and using it. Automation can then replicate and improve these actions independently.


Are you ready to apply Make sure you understand all the responsibilities and tasks associated with this role before proceeding.

Complexio is a joint venture between Hafnia and Símbolo, in partnership with Marfin ManagementC Transport MaritimeTrans Sea Transport and BW Epic Kosan

 

About the job

As a DevOps engineer at our AI product company, you will define and create the platform for deploying, managing, and optimizing our distributed systems across on-premises, multiple cloud environments (AWS, Azure, Google Cloud), and Kubernetes.

Our system leverages multiple LLMs, Graph and Vector Databases and integrates data from multiple sources to power our AI solutions. You will ensure our infrastructure is robust, scalable, and secure, supporting the seamless delivery of our innovative products. This role requires combining cloud technologies and database management expertise, embracing the challenges of integrating AI and machine learning workflows on modern GPUs.

Responsibilities

  • Preferred M.Sc or Ph.d degree in Computer Science or a related field
  • At least 7 years of experience deploying and managing cloud infrastructure (AWS, Azure, Google Cloud) 
  • At least 3 years experience in working with kubernetes environments
  • Proficient in managing and scaling Kubernetes clusters, including monitoring, troubleshooting, and ensuring high availability
  • Experience with cloud-native technologies, CI/CD pipelines, and containerization tools (e.g., Docker)
  • Familiarity with data integration and management from multiple sources in a distributed system environment
  • Proficiency in at least one programming language (Python, Java, Go), and experience with scripting for automation
  • Strong understanding of network infrastructure and security principles, ensuring compliance with data protection regulations

A Bonus:

  • Proficient in database management, specifically with Neo4j and vector databases, including setup, scaling, and optimization for performance and reliability
  • Experience deploying and running Machine Learning Solutions, including LLMs
  • Remote working (Remote must be within 3-5 hours of CET timezone)

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.