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- Tasks: Architect and maintain AI content production systems, optimising workflows and automation tools.
- Company: Join a pioneering company revolutionising digital marketing with AI-powered content generation.
- 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 cutting-edge projects.
- Qualifications: 5+ years in Python automation, experience with Stable Diffusion, and cloud infrastructure management required.
- Other info: Opportunity to influence the roadmap from images to next-gen AI video creation.
The predicted salary is between 48000 - 72000 £ per year.
Senior AI Infrastructure/Workflow Engineer
2 days ago Be among the first 25 applicants
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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
- 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
- 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
- Analyze generation outputs, synthesize quality metrics, and recommend iterative improvements
- Build tools for rapid A/B comparisons, anomaly detection, and content selection at scale
- 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
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Industries
Hospitals and Health Care, Non-profit Organizations, and Government Administration
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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 AI content generation. Being well-versed in these technologies will not only help you during interviews but also demonstrate your genuine interest in the role.
✨Tip Number 2
Network with professionals in the AI and tech industry, especially those who have experience in cloud infrastructure and automation. Engaging in discussions or attending relevant meetups can provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Showcase your hands-on experience by contributing to open-source projects related to AI workflows or cloud infrastructure. This not only enhances your skills but also gives you practical examples to discuss during interviews.
✨Tip Number 4
Prepare to discuss specific challenges you've faced in previous roles, particularly around automation and scaling processes. Highlighting your problem-solving skills and how you've optimised workflows will set you apart from other candidates.
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 your experience with Python automation, Stable Diffusion, and GPU cloud infrastructure. Use specific examples that demonstrate your hands-on experience and achievements in these areas.
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 relevant projects you've worked on and how they relate to the role of Senior AI Infrastructure/Workflow Engineer.
Showcase Relevant Projects: If you have worked on projects involving image or video generation pipelines, be sure to include them in your application. Describe your role, the technologies used, and the impact of your work on the project's success.
Highlight Collaboration Skills: Since the role involves cross-functional collaboration, emphasise your ability to work with creative and technical teams. Provide examples of how you've successfully collaborated in past roles to achieve common 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, especially those involving Stable Diffusion or similar technologies.
✨Demonstrate Problem-Solving Abilities
Expect questions that assess your problem-solving skills. Prepare examples of challenges you've faced in previous roles, particularly related to cloud infrastructure or data processing, and how you overcame them.
✨Familiarise Yourself with the Company’s Tech Stack
Research the tools and technologies used by the company, such as Terraform, Kubernetes, or Docker. Being knowledgeable about their tech stack will show your genuine interest and help you engage in more meaningful discussions during the interview.
✨Prepare for Cross-Functional Collaboration Questions
Since the role involves working closely with creative and product teams, be ready to discuss your experience in cross-functional collaboration. Share examples of how you've aligned technical projects with business goals and mentored junior engineers.
