Senior DevOps Engineer

Complexio
Newcastle upon Tyne
1 year ago
Applications closed

Related Jobs

View all jobs

Senior MLOps Engineer

Senior DataOps Engineer

Senior MLOps Engineer

Senior Machine Learning Engineer

Senior Machine Learning Operations Engineer

Senior Machine Learning Operations Engineer

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.


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.

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.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.