Pavago
Staffing and Recruiting
Full-StackAIEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Full-Stack AI Engineer at Pavago. Skills: Full-Stack Development, AI/ML Integration, LLM Systems, Cloud Infrastructure. Deploy AI/ML models. Integrate AI/ML models”
What You'll Achieve.
Build scalable systems; Turn AI capabilities into products; Deliver AI-powered workflows; Deliver intelligent automation systems; Deliver chat experiences; Deliver analytics tools; Deliver scalable ML infrastructure; Ship AI features; Reduce manual workflows; Adopt AI features; Usage of AI features; Achieve scalable architecture; Achieve maintainable architecture; Achieve cost-efficient architecture; Successful deployment of AI features; Maintain application uptime; Maintain infrastructure reliability; Fast inference performance; Stable inference performance
Industry & Context.
Critical thinking; Troubleshoot production incidents; Troubleshoot system bottlenecks
What They're Looking For.
Must Have
3+ years software engineering, AI/ML exposure, Python proficiency, JavaScript/TypeScript proficiency, PyTorch or TensorFlow experience, Deploy ML/LLM systems, React, Next.js, or Vue frontend experience, Build APIs and backend services, SQL skills, Cloud data platforms experience, Docker familiarity, CI/CD pipelines familiarity, Cloud deployments familiarity
Nice to Have
AI-powered SaaS platforms experience, Automation products experience, LLM fine-tuning experience, Embeddings experience, RAG systems experience, Vector databases familiarity, Semantic search infrastructure familiarity, MLOps tools experience, Microservices knowledge, Serverless architectures knowledge, Distributed systems knowledge, Inference cost optimization experience, Inference performance optimization experience
What You'll Do.
Integrate AI/ML models
Develop retrieval-augmented generation pipelines
Implement semantic search
Implement AI-powered workflows
Optimize inference performance
Optimize inference latency
Optimize inference cost efficiency
Build frontend interfaces
Develop backend systems
Connect AI models with business logic
Create user-facing AI features
Ensure applications are responsive
Ensure applications are secure
Ensure applications are scalable
Ensure applications are production-ready
Build scalable backend architectures
Develop ETL pipelines
Automate preprocessing
Automate data labeling
Automate workflow orchestration
Manage structured datasets
Manage unstructured datasets
Maintain pipelines for model training
Maintain pipelines for model fine-tuning
Maintain pipelines for model evaluation
Containerize AI services
Deploy applications using Kubernetes
Deploy applications using cloud infrastructure
Build CI/CD pipelines for model deployments
Build CI/CD pipelines for application releases
Monitor model performance
Monitor system reliability
Work with cloud platforms
Improve infrastructure efficiency
Implement secure API authentication
Implement access control
Implement rate limiting
Ensure AI systems comply with GDPR
Ensure AI systems comply with HIPAA
Ensure AI systems comply with SOC 2
Maintain observability
Troubleshoot production incidents
Optimize system reliability
Partner with product teams
Partner with data teams
Define AI-powered product features
Translate AI prototypes into production systems
Participate in sprint planning
Participate in technical discussions
Participate in architecture decisions
Maintain technical documentation
Maintain reproducible workflows
How You'll Work.
Team & Collaboration
Collaborate with engineering teams; Collaborate with product teams; Collaborate with data teams; Cross-functional teams
Communication Scope
Clear communication; Effective communication
Process & Methodology
Sprint planning, Architecture decisions
Full Job Description
### **Full-Stack AI Engineer** **Position Type:** Full-Time, Remote **Working Hours:** U.S. Business Hours **Location:** Remote (LATAM, Eastern Europe, Pakistan, India, South Africa Preferred) ### **About the Role** We are hiring a highly skilled Full-Stack AI Engineer to build, deploy, and scale AI-powered applications that solve real business problems. This role combines full-stack software engineering with applied AI/ML expertise. You will work across backend systems, AI pipelines, APIs, cloud infrastructure, and frontend applications to bring AI features from prototype to production. The ideal candidate is both technically strong and product-minded — someone who can move quickly, build scalable systems, and turn modern AI capabilities into reliable, user-friendly products. You will collaborate closely with engineering, product, and data teams to deliver AI-powered workflows, intelligent automation systems, chat experiences, analytics tools, and scalable machine learning infrastructure. ### **What You’ll Own** ### **AI & LLM Integration** • Deploy and integrate AI/ML models using OpenAI, Hugging Face, TensorFlow, PyTorch, or similar frameworks • Build scalable APIs for AI inference using FastAPI, Flask, or Node.js • Develop retrieval-augmented generation (RAG) pipelines using Pinecone, Weaviate, FAISS, or vector databases • Implement embeddings, semantic search, and AI-powered workflows • Optimize inference performance, latency, and cost efficiency ### **Full-Stack Application Development** • Build frontend interfaces using React, Next.js, Vue, or modern JavaScript frameworks • Develop backend systems and APIs that connect AI models with business logic • Create user-facing AI features such as chatbots, copilots, dashboards, and automation tools • Ensure applications are responsive, secure, scalable, and production-ready • Build microservices and scalable backend architectures ### **Data Engineering & Pipelines** • Develop ETL pipelines for ingesting, cleaning, tr
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