Full-Stack AI Engineer

Pavago

22h • Remote

About The Position

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.

Requirements

• 3+ years of software engineering experience with AI/ML exposure
• Strong proficiency in Python and JavaScript/TypeScript
• Experience with AI/ML frameworks such as PyTorch or TensorFlow
• Experience deploying ML or LLM systems into production environments
• Strong frontend experience with React, Next.js, or Vue
• Experience building APIs and backend services
• Strong SQL skills and experience with cloud data platforms
• Familiarity with Docker, CI/CD pipelines, and cloud deployments

Nice To Haves

• Experience building AI-powered SaaS platforms or automation products
• Experience with LLM fine-tuning, embeddings, and RAG systems
• Familiarity with vector databases and semantic search infrastructure
• Experience with MLOps tools such as MLflow, Kubeflow, Vertex AI, or SageMaker
• Knowledge of microservices, serverless architectures, and distributed systems
• Experience optimizing inference cost and performance at scale

Responsibilities

• 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
• 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
• Develop ETL pipelines for ingesting, cleaning, transforming, and managing datasets
• Automate preprocessing, data labeling, and workflow orchestration using Airflow, Prefect, or Dagster
• Manage structured and unstructured datasets in cloud environments
• Maintain reliable pipelines for model training, fine-tuning, and evaluation
• Containerize AI services using Docker and deploy applications using Kubernetes or cloud infrastructure
• Build CI/CD pipelines for model deployments and application releases
• Monitor model performance, drift, costs, and system reliability
• Work with cloud platforms such as AWS, GCP, Azure, Vertex AI, or SageMaker
• Improve scalability, uptime, and infrastructure efficiency
• Implement secure API authentication, access control, and rate limiting
• Ensure AI systems comply with GDPR, HIPAA, SOC 2, or related compliance requirements
• Maintain monitoring, logging, and observability for production systems
• Troubleshoot production incidents and optimize system reliability
• Partner with product and data teams to define AI-powered product features
• Translate AI prototypes into scalable production systems
• Participate in sprint planning, technical discussions, and architecture decisions
• Maintain clear technical documentation and reproducible workflows

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed