Position Overview
We are seeking a cost-focused AI & Automation Developer specializing in building ultra-efficient, low-cost generative AI automation workflows. Your primary mission is to create automated content generation pipelines (scripts, images, videos) that maximize output quality while minimizing operational costs. This role requires deep expertise in cost optimization strategies, API provider comparison, and building scalable generative AI workflows that deliver exceptional ROI.
Key Responsibilities
Cost-Optimized Generative AI Workflows
- Build end-to-end automation pipelines for content generation with target costs under $0.2-$0.25 per output
- Design multi-modal workflows combining text generation, image creation, and video production
- Implement cost monitoring and optimization strategies across all generative AI operations
- Compare and migrate between AI service providers (OpenAI, FAL.AI, Stability AI, Runway, etc.) based on cost-performance analysis
- Build failover systems and provider switching logic to maintain cost targets
Workflow Automation & Integration
- Develop and maintain complex automation workflows using n8n and similar platforms
- Design and implement API aggregation solutions to connect multiple services and data sources
- Build end-to-end automation pipelines that integrate various AI models, APIs, and third-party services
- Optimize existing workflows for cost efficiency and performance improvements
- Troubleshoot and resolve automation workflow issues and bottlenecks
AI Model Integration & Cost Management
- Research, test, and implement the most cost-effective AI models for specific generative tasks
- Build dynamic model selection systems that automatically choose optimal providers based on real-time pricing
- Integrate various generative AI APIs: text generation (GPT, Claude, Llama), image generation (FLUX, DALL-E, Midjourney), video generation (Runway, Pika, Kling)
- Implement batch processing and queue management to leverage bulk pricing and rate limits
- Monitor API costs in real-time and implement automatic cost controls and alerts
Infrastructure & Cloud Management
- Deploy and manage cloud instances on platforms like RunPod, Cloudflare or GCP
- Configure and optimize cloud GPU and CPU resources for AI workloads
- Set up and maintain scalable infrastructure for automation workflows
- Monitor resource usage and implement cost optimization strategies
Database & Data Architecture
- Design and implement database schemas to support automation workflows
- Build data pipelines for ingesting, processing, and storing workflow data
- Optimize database performance for high-volume automation processes
- Implement data validation and quality assurance measures
- Generative Content Pipeline Development
- Create automated script generation workflows for various content types and formats
- Build image generation pipelines with prompt optimization and style consistency
- Develop video generation workflows combining multiple AI models (text-to-image-to-video)
- Implement content quality assurance and filtering systems
- Build template and prompt libraries for consistent, cost-effective content generation
Project Management & Cost Analysis
- Analyze existing workflows and identify cost reduction opportunities without quality loss
- Create detailed cost breakdowns and ROI analysis for automation workflows
- Develop testing frameworks for comparing AI provider costs and quality metrics
- Document workflows, APIs, and system architectures
- Collaborate with stakeholders to understand requirements and deliver solutions
Required Skills & Experience
Technical Skills
- Cost-Optimized Automation: 3+ years building low-cost, high-volume automation workflows
- Generative AI Integration: Deep experience with text, image, and video generation APIs
- Provider Cost Analysis: Proven track record of reducing AI operational costs through strategic provider selection
- n8n Workflow Development: Advanced proficiency in building complex, multi-step generative AI workflows
- API Cost Management: Experience with rate limiting, batch processing, and cost monitoring systems
- Cloud Resource Optimization: Expertise in cost-effective GPU/CPU provisioning and scaling
Specialized Experience
- Multi-Modal Content Generation: Building workflows that combine text, image, and video generation
- Cost Per Unit Optimization: Achieving specific cost targets Provider Migration: Successfully migrating workflows between AI providers to reduce costs
- Generative AI Prompt Engineering: Optimizing prompts for quality and token efficiency
- Batch Processing Systems: Implementing queue management and bulk processing for cost savings
- Real-time Cost Monitoring: Building dashboards and alerts for AI spend management
Soft Skills
- Cost-Conscious Mindset: Natural ability to balance quality requirements with cost constraints
- Analytical Problem Solving: Data-driven approach to optimization and decision making
- Rapid Prototyping: Ability to quickly test and iterate on new AI models and providers
- Quality vs. Cost Trade-off Analysis: Expertise in making strategic decisions about acceptable quality thresholds
Preferred Qualifications
- Knowledge of machine learning concepts and model deployment
- Experience with video/audio processing workflows
- FFmpeg experience
- Familiarity with monitoring and logging tools
- Previous expertise in cost optimization for AI/ML workloads
What You'll Work On
- Ultra-Low-Cost Content Generation: Build automated systems that produce high-quality scripts, images, and videos at breakthrough cost points
- Provider Optimization: Continuously research and migrate between AI providers to maintain cost leadership
- Scalable Generative Pipelines: Design workflows that can generate thousands of pieces of content daily while maintaining sub-dollar costs per item
- Quality-Cost Balance: Develop testing frameworks to ensure cost reductions don't compromise content quality standards
Compensation & Benefits
- Competitive salary with significant performance $2000
- Cost Savings Bonus: Earn up to 25% salary bonus quarterly for achieving aggressive cost reduction targets
- Professional development budget focused on emerging generative AI technologies
- Access to premium AI service credits for testing and optimization
Application Requirements
Please submit:
- Resume highlighting specific cost optimization achievements in generative AI workflows
- Cost Performance Portfolio: Examples of workflows you've built with detailed cost breakdowns (cost per output, before/after optimization metrics)
- Case study of a successful AI provider migration or cost reduction project
- Links to n8n workflows, automation scripts, or cost monitoring dashboards you've built
- Brief explanation of your philosophy on balancing quality vs. cost in generative AI applications
Bonus Points:
- Provide actual cost-per-unit metrics from workflows you've optimized
- Show examples of multi-modal content generation pipelines
- Demonstrate experience with at least 3 different generative AI providers
