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- Tasks: Design and optimise AI content production systems, focusing on image and video generation.
- Company: Join a pioneering company revolutionising digital marketing with AI-powered content creation technologies.
- Benefits: Enjoy a fully remote role with a flexible schedule and competitive pay.
- Why this job: Shape the future of AI influencers while collaborating with a passionate team on high-impact projects.
- Qualifications: 5+ years in Python automation, experience with Stable Diffusion, and strong cloud infrastructure skills.
- Other info: Opportunity to influence the roadmap from images to next-gen AI video creation.
The predicted salary is between 48000 - 84000 ÂŁ per year.
Senior AI Infrastructure/Workflow Engineer 2 days ago Be among the first 25 applicants Get AI-powered advice on this job and more exclusive features. Job Description We\’re pioneering the next generation of AI-powered content creation technologies. Using advanced image generation pipelines, custom workflows, and proprietary tooling, we generate, curate, and scale hundreds of thousands of images weekly—soon expanding into video. Our mission is to revolutionize digital marketing through AI-powered content generation at scale, delivering personalized engagement across platforms backed by enterprise-grade cloud infrastructure. Role Overview: As a top engineer, you will architect, build, and maintain the end‑to‑end systems powering our AI content production platform. You’ll design and optimize Stable Diffusion training and inference workflows, develop and manage automation tools (local and cloud), and scale GPU instances to create tens of millions of assets. You’ll balance coding, systems design, and data analysis to push our platform’s performance, reliability, and feature set forward. Key Responsibilities Model & Workflow Development Train and fine‑tune Stable Diffusion checkpoints, LoRAs, and custom datasets at scale Design and maintain ComfyUI graphs and custom nodes for efficient batch generation Prototype new AI-video tooling leveraging image workflows as foundational blocks Automation & Tooling Author robust Python scripts and services to review, sort, tag, and organize huge quantities of images/day Implement multi‑processing, threading, and distributed batch pipelines for speed and reliability Build dashboard backends and lightweight frontends to monitor job status, results, and metrics Cloud Infrastructure & Architecture Help deploy, manage, and optimize GPU cloud instances Automate provisioning, scaling, and health‑checks (IaC tools like Terraform, Ansible, or similar) Design cost‑effective, high‑throughput data storage and transfer strategies between on‑prem & cloud Data Review & Analysis Analyze generation outputs, synthesize quality metrics, and recommend iterative improvements Build tools for rapid A/B comparisons, anomaly detection, and content selection at scale Cross‑Functional Collaboration Work closely with creative, product, and leadership teams to align technical roadmap with business goals Document processes, share best practices, and mentor junior engineers as the team grows Required Qualifications 5+ years of hands‑on experience in Python automation and scripting (large‑scale batch processing) Deep familiarity with Stable Diffusion training/inference, LoRA methods, and checkpoint management Proven track record building and optimizing custom ComfyUI workflows or similar node‑based systems Expertise deploying and managing GPU‑accelerated cloud infrastructure Strong understanding of distributed processing, concurrency (multiprocessing, threading, async) Solid foundation in Linux server administration and CI/CD pipelines Excellent problem‑solving skills, self‑starter attitude, and ability to operate independently Preferred Qualifications Experience architecting scalable either image or video generation related pipelines Familiarity with frontend frameworks for lightweight dashboarding Hands‑on with Terraform, Kubernetes, or Docker‑Swarm for container orchestration Background in data engineering / ETL processes for large multimedia datasets Prior work in AI content moderation, classification, or metadata tagging Content Analytics: Experience implementing automated content quality assessment and performance analytics Data Pipeline Experience: Background in building robust data pipelines for training, fine-tuning, and continuous model improvement What You’ll Get Architecting high‑impact projects driving the future of AI influencers Fully remote, flexible schedule; collaborate with a lean, passionate team Competitive pay package Access/budget(s) to any cutting‑edge resources Opportunity to shape the roadmap from images to next‑gen AI video creation Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job function Job function Information Technology Industries Hospitals and Health Care, Non-profit Organizations, and Government Administration Referrals increase your chances of interviewing at Braintrust by 2x Get notified about new Senior Infrastructure Engineer jobs in United Kingdom . City Of London, England, United Kingdom 1 month ago London, England, United Kingdom 3 months ago Blackburn, England, United Kingdom 1 week ago Warrington, England, United Kingdom 1 week ago City Of London, England, United Kingdom 1 month ago We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI. #J-18808-Ljbffr
Senior AI Infrastructure/Workflow Engineer employer: Braintrust
Contact Detail:
Braintrust Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AI Infrastructure/Workflow Engineer
✨Tip Number 1
Familiarise yourself with the latest advancements in Stable Diffusion and LoRA methods. Being able to discuss recent developments or share your insights during interviews can demonstrate your passion and expertise in the field.
✨Tip Number 2
Showcase your experience with cloud infrastructure by preparing examples of how you've optimised GPU instances in previous roles. This will help you stand out as someone who can directly contribute to our AI content production platform.
✨Tip Number 3
Network with professionals in the AI and tech community, especially those who have worked on similar projects. Engaging in discussions about AI content generation can provide valuable insights and potentially lead to referrals.
✨Tip Number 4
Prepare to discuss your problem-solving approach in detail. We value engineers who can think critically and independently, so be ready to share specific examples of challenges you've faced and how you overcame them.
We think you need these skills to ace Senior AI Infrastructure/Workflow Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in Python automation, Stable Diffusion, and cloud infrastructure. Use specific examples that demonstrate your expertise in building and optimising workflows.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI content generation and how your skills align with the company's mission. Mention any previous projects that relate to image or video generation pipelines.
Showcase Problem-Solving Skills: Include examples of how you've tackled complex problems in past roles, particularly in relation to distributed processing and automation. This will demonstrate your ability to operate independently and effectively.
Highlight Collaboration Experience: Since the role involves cross-functional collaboration, mention any experiences where you've worked closely with creative or product teams. This shows you can align technical work with business goals.
How to prepare for a job interview at Braintrust
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with Python automation and scripting. Highlight specific projects where you've implemented large-scale batch processing, as this is crucial for the role.
✨Demonstrate Your Knowledge of AI Workflows
Familiarise yourself with Stable Diffusion training and inference processes. Be ready to explain how you've optimised workflows or built custom ComfyUI systems in previous roles.
✨Discuss Cloud Infrastructure Experience
Talk about your experience with GPU-accelerated cloud infrastructure. Mention any tools like Terraform or Ansible that you've used for automating provisioning and scaling, as this will be key to the position.
✨Prepare for Problem-Solving Scenarios
Expect to face technical challenges during the interview. Prepare to discuss how you've approached problem-solving in past projects, particularly in relation to distributed processing and data analysis.
