Engineering Manager - Infrastructure

Complexio
1 month ago
Applications closed

Related Jobs

View all jobs

Engineering Manager

Analytics Engineering Manager

Software Engineering Manager | £110k – Java, Vue.js & AWS

Data Engineering Manager

MLOps Engineering Manager

Machine Learning Engineering Manager | Computer Vision | Deep Learning | Python | C++ | London, Hybrid

About Complexio

Complexio's Foundational AI automates business activities by ingesting entire company data—both structured and unstructured—to extract meaningful insights. Our proprietary models and algorithms develop a deep understanding of human interactions with data, enabling automation to replicate and enhance these processes independently.

Complexio is a joint venture between Hafnia and Símbolo, in partnership with Marfin Management, C Transport Maritime, Trans Sea Transport, and BW Epic Kosan.

About the Role

As an Engineering Manager  you will play a key role in leading infrastructure projects, supporting AI-powered applications, and working closely with clients to ensure smooth deployment and integration. This role is ideal for someone with strong technical foundations in cloud, DevOps, and automation, who is also looking to grow their leadership skills while working on real-world AI infrastructure challenges.

You will collaborate with Software Engineers, Data Scientists, DevOps, and clients to ensure system reliability, efficient cloud-native deployments, and seamless client onboarding. This is a hands-on leadership role, where you will balance technical execution, project coordination, and stakeholder management.

Requirements

Infrastructure & Operations

  • Support the design and scaling of cloud-based infrastructure, ensuring security, cost-efficiency, and high availability.
  • Implement and maintain CI/CD pipelines, automating deployments for efficiency and reliability.
  • Oversee monitoring, observability, and logging, ensuring system health and uptime.
  • Manage incident response and disaster recovery planning, ensuring fast recovery and minimal downtime.
  • Work with security best practices, including IAM, data encryption, and compliance requirements.

Professional Services

  • Collaborate with clients to understand their technical needs and ensure successful deployment of AI-powered solutions.
  • Provide technical support and guidance to clients during onboarding, integration, and troubleshooting.
  • Work closely with business and product teams to align infrastructure solutions with client requirements.
  • Develop documentation and training materials to help internal teams and clients effectively use our platforms.

Leadership & Growth

  • Act as a bridge between technical and business teams, ensuring smooth communication and alignment.
  • Mentor and support engineers, helping them grow their expertise in cloud, DevOps, and automation.
  • Lead small projects and develop leadership skills by taking ownership of critical technical initiatives.
  • Stay up to date with emerging technologies in cloud infrastructure, automation, and AI.

What We’re Looking For:

Technical & Leadership Skills

  • 2–5 years of experience in leadership across infrastructure, DevOps, or site reliability engineering (SRE).
  • Experience working with cloud platforms (AWS, Azure, GCP) and container orchestration (Kubernetes, Docker, ECS).
  • Hands-on experience with infrastructure as code (IaC) tools such as Terraform, Pulumi, or CloudFormation.
  • Strong understanding of CI/CD automation, using tools like GitHub Actions, ArgoCD, or Jenkins.
  • Knowledge of monitoring and observability tools such as Prometheus, Grafana, Datadog, or OpenTelemetry.
  • Experience with databases and storage solutions like Postgres, Redis, Neo4j, or MongoDB.
  • Basic knowledge of networking, security, and identity management.
  • Comfortable engaging with clients and stakeholders, with good communication skills.
  • Interest in growing into a leadership role, with a willingness to take on more responsibility over time.

Bonus Skills

  • Experience with customer-facing technical roles (e.g., technical consulting, customer success, professional services).
  • Familiarity with AI Ops and MLOps, managing AI models in production.
  • Experience with scripting and automation (Python, Go, Bash).
  • Knowledge of FinOps and cost optimization in cloud environments.

Benefits

  • Get hands-on experience in AI-powered infrastructure at a fast-moving company.
  • Develop leadership skills in a supportive environment while still working on technical challenges.
  • Work closely with clients, learning how AI-driven automation is transforming industries.
  • Remote-friendly role (must be within 4–5 hours of CET timezone).

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Jobs

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

Jobs Careers

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Jobs

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.