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 AI, Machine Learning, LLM Systems, Cloud Infrastructure. Deploy ML/LLM models. Integrate ML/LLM models”
What You'll Achieve.
Successful deployment AI features; Application uptime >= 99.9%; Inference latency below targets; Reduction manual workflows; Stable model performance; Minimized drift/degradation; Positive adoption/engagement; Scalable infrastructure; Maintainable infrastructure; Cost-efficient infrastructure
Industry & Context.
Analytical; Solutions-oriented; Debugging; Optimization
What They're Looking For.
Must Have
3+ years software engineering, AI/ML exposure, Python proficiency, JavaScript/TypeScript proficiency, Deploy AI/ML models production, Front-end experience, SQL skills, Cloud data warehouses experience, Familiarity with REST APIs, Familiarity with microservices, Familiarity with distributed systems, Docker experience, CI/CD workflows experience, Cloud infrastructure experience
Nice to Have
Building/scaling AI SaaS applications, Embeddings understanding, Vector databases understanding, RAG architectures understanding, LLM fine-tuning experience, Evaluation experience, Prompt optimization experience, MLOps tools familiarity, Serverless architectures experience, Cost-optimized inference systems experience, SaaS background, Automation platforms background, Analytics systems background, AI-driven products background
What You'll Do.
Integrate ML/LLM models
Build AI inference APIs
Implement RAG pipelines
Optimize prompt engineering
Optimize AI workflows
Build front-end applications
Develop back-end services
Design scalable architectures
Ensure applications are intuitive
Ensure applications are secure
Ensure applications are responsive
Ensure applications are production-ready
Automate data preprocessing
Automate data versioning
Automate data labeling
Automate pipeline orchestration
Maintain reliable data flows
Containerize AI services
Build CI/CD pipelines
Maintain CI/CD pipelines
Monitor inference latency
Monitor application performance
Support cloud infrastructure
Ensure AI systems comply
Implement authentication
Implement access control
Implement rate limiting
Implement secure API practices
Collaborate with product managers
Collaborate with designers
Collaborate with data scientists
Participate in sprint planning
Participate in architecture discussions
Participate in code reviews
Maintain clear documentation
How You'll Work.
Team & Collaboration
Cross-functional teams; Technical teams; Non-technical teams; Product managers; Designers; Data scientists; Engineering teams; Product teams
Communication Scope
Collaborative communicator
Process & Methodology
Sprint planning, Sprint schedules
Full Job Description
### **Job Title: Full-Stack AI Engineer** **Position Type:** Full-Time, Remote **Working Hours:** U.S. client business hours (with flexibility for deployments, experimentation cycles, and sprint schedules) ### **About the Role** Our client is seeking a highly skilled Full-Stack AI Engineer to design, build, and deploy scalable AI-powered applications that solve real-world business problems. This role bridges software engineering with applied machine learning, combining front-end development, back-end systems, AI model integration, and cloud infrastructure into production-ready applications. You will work across the full product lifecycle — from experimentation and prototyping to deployment, optimization, and monitoring. The ideal candidate is both technically strong and execution-focused, capable of building AI-driven systems that are scalable, reliable, performant, and user-friendly. ### **Responsibilities** ### **AI Model Integration & LLM Systems** • Deploy and integrate pre-trained and fine-tuned ML / LLM models using OpenAI, Hugging Face, TensorFlow, PyTorch, or similar frameworks • Build scalable AI inference APIs using FastAPI, Flask, Node.js, or similar technologies • Implement retrieval-augmented generation (RAG) pipelines using vector databases such as Pinecone, Weaviate, Chroma, or FAISS • Optimize prompt engineering, embeddings, and AI workflows for performance, accuracy, and cost efficiency ### **Full-Stack Application Development** • Build responsive front-end applications using React, Next.js, Vue, or similar frameworks • Develop back-end services and APIs connecting AI systems to business workflows and user-facing applications • Design scalable architectures for chatbots, AI assistants, analytics dashboards, search systems, and workflow automation tools • Ensure applications are intuitive, secure, responsive, and production-ready ### **Data Engineering & Pipeline Development** • Build ETL/ELT pipelines for ingesting, cleaning, transforming, and proce
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