Full-Stack AI Engineer
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, 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
Infrastructure, DevOps & MLOps
- 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
Security, Compliance & Reliability
- 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
Collaboration & Product Development
- 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 Makes You a Great Fit
- You are both a strong software engineer and a hands-on AI builder
• You enjoy shipping AI-powered features that solve real-world business problems
• You are comfortable moving from prototype to production independently
• You think critically about scalability, performance, cost, and usability
• You stay current with rapidly evolving AI tools, frameworks, and infrastructure
• You communicate clearly and collaborate effectively across technical and non-technical teams
Required Experience & Skills
- 3+ years of software engineering experience with AI/ML exposure
• Strong proficiency in Python and JavaSc