Senior Software Engineer

AGITProp
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Software Engineer (GO/PHP)

Senior Software Engineers

Senior C++ Software Engineer, Stats, Maths

Senior Embedded Software Engineer - UEFI

Senior Embedded Linux Engineer

Senior Go Engineer

Newly founded, AGITProp is an AI-driven quant research firm that is pushing the boundaries of algorithmic trading.Quant firms have leveraged AI and ML for years, but the increasing complexity and scale of global markets demand a more comprehensive and integrated approach.At AGITProp, we are leveraging the latest advances and insights from foundation and large language models (LLM) to build novel models across multiple modalities. We have ambitious growth plans and are searching for the best and brightest minds from across tech and finance to help us achieve our aim.About the RoleWe are seeking a highly skilled Senior Software Engineer (Python) with a strong DevOps mindset. Given our current team size, we believe a dedicated DevOps role isn't necessary at this time.Therefore, we are looking for a strong Python coder who is comfortable and enthusiastic about contributing to infrastructure and DevOps tasks alongside their core software engineering responsibilities.The ideal candidate will possess a strong foundation in Python programming, a deep understanding of DevOps principles, experience with automation tools, and familiarity with cloud technologies. You will play a crucial role in building and scaling our infrastructure as we grow.Responsibilities:Infrastructure as Code: Design and implement infrastructure as code solutions using tools like Terraform, Ansible, or Puppet.Cloud and Containerization: Leverage cloud platforms (AWS, Azure, GCP, etc.) and containerization technologies like Docker to build scalable and resilient systems.CI/CD Pipelines: Create and maintain efficient CI/CD pipelines using tools like Github CI, Jenkins, GitLab CI/CD, or CircleCI.Monitoring and Alerting: Implement robust monitoring and alerting systems to proactively identify and resolve issues. Grafana preferred.Security: Prioritize security best practices and implement measures to protect our infrastructure.Requirements:Programming Proficiency: Strong Python programming skills.Linux Expertise: Strong Linux system administration skills.Infrastructure as Code: Experience with infrastructure as code principles and tools.Cloud Experience: Experience with cloud platforms (AWS, Azure, GCP, etc.).Big Data: Experience with big data frameworks like Apache Spark.Preferred Qualifications:Automation Tools: Experience with automation tools like Jenkins, GitLab CI/CD, CircleCI, Terraform, Ansible, Puppet, or similar.Big Data and Machine Learning: Experience with GPU-accelerated computing.Nebius Experience: Experience with Nebius platform.Security: Experience with security tools and best practices.Certifications: Relevant certifications (e.G., Cloud computing, Kubernetes, etc.).We appreciate there isn’t a lot of information to go off from a company perspective. However, we can be very open about this and what we are looking to achieve throughout the screening and interview phase of the recruitment process.AGITProp, we believe the power of AI lies in its diversity, just like the teams who build it. We are committed to fostering a welcoming and inclusive environment where individuals from all backgrounds and experiences can thrive. We understand that a diverse workforce leads to richer perspectives, more innovative solutions, and ultimately, better results.If this position is something that you are interested in, to apply, please submit your resume, brief cover letter, and any relevant publications or research work that might be of interest.If this role isn’t exactly what you are looking for but feel you could add value and are interested in hearing more, please check out any other relevant roles across the company. We have several openings and would love to speak to anyone who has a background in quantitative finance and AI.

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.

10 Ways AI Pros Stay Inspired: Boost Creativity with Side Projects, Hackathons & More

In the rapidly evolving world of Artificial Intelligence (AI), creativity and innovation are critical. AI professionals—whether data scientists, machine learning engineers, or research scientists—must constantly rejuvenate their thinking to solve complex challenges. But how exactly do these experts stay energised and creative in their work? The answer often lies in a combination of strategic habits, side projects, hackathons, Kaggle competitions, reading the latest research, and consciously stepping out of comfort zones. This article will explore why these activities are so valuable, as well as provide actionable tips for anyone looking to spark new ideas and enrich their AI career. Below, we’ll delve into tried-and-tested strategies that AI pros employ to drive innovation, foster creativity, and maintain an inspired outlook in an industry that can be both exhilarating and daunting. Whether you’re just starting your AI journey or you’re an experienced professional aiming to sharpen your skills, these insights will help you break out of ruts, discover fresh perspectives, and bring your boldest ideas to life.

Top 10 AI Career Myths Debunked: Key Facts for Aspiring Professionals

Artificial Intelligence (AI) is one of the most dynamic and rapidly growing sectors in technology today. The lure of AI-related roles continues to draw a diverse range of job seekers—from seasoned software engineers to recent graduates in fields such as mathematics, physics, or data science. Yet, despite AI’s growing prominence and accessibility, there remains a dizzying array of myths surrounding careers in this field. From ideas about requiring near-superhuman technical prowess to assumptions that machines themselves will replace these jobs, the stories we hear sometimes do more harm than good. In reality, the AI job market offers far more opportunities than the alarmist headlines and misconceptions might suggest. Here at ArtificialIntelligenceJobs.co.uk, we witness firsthand the myriad roles, backgrounds, and success stories that drive the industry forward. In this blog post, we aim to separate fact from fiction—taking the most pervasive myths about AI careers and debunking them with clear, evidence-based insights. Whether you are an established professional considering a career pivot into data science, or a student uncertain about whether AI is the right path, this article will help you gain a realistic perspective on what AI careers entail. Let’s uncover the truth behind the most common myths and discover the actual opportunities and realities you can expect in this vibrant sector.

Global vs. Local: Comparing the UK AI Job Market to International Landscapes

How to navigate salaries, opportunities, and work culture in AI across the UK, the US, Europe, and Asia Artificial Intelligence (AI) has evolved from a niche field of research to an integral component of modern industries—powering everything from chatbots and driverless cars to sophisticated data analytics in finance and healthcare. The job market for AI professionals is consequently booming, with thousands of new positions posted each month worldwide. In this blog post, we will explore how the UK’s AI job market compares to that of the United States, Europe, and Asia, delving into differences in job demand, salaries, and workplace culture. Additionally, we will provide insights for candidates considering remote or international opportunities. Whether you are a freshly qualified graduate in data science, an experienced machine learning engineer, or a professional from a parallel domain looking to transition into AI, understanding the global vs. local landscape can help you make an informed decision about your career trajectory. As the demand for artificial intelligence skills grows—and borders become more porous with hybrid and remote work—the possibilities for ambitious job-seekers are expanding exponentially. This article will offer a comprehensive look at the various regional markets, exploring how the UK fares in comparison to other major AI hubs. We’ll also suggest factors to consider when choosing where in the world to work, whether physically or remotely. By the end, you’ll have a clearer picture of the AI employment landscape, and you’ll be better prepared to carve out your own path.