Full-Stack AI Engineer
Full-Stack AI Engineer – Remote
AI Engineering | LLMs | Python | React | MLOps | Cloud Infrastructure
Position Type: Full-Time, Remote
Working Hours: U.S. Client Business Hours (with flexibility for sprint planning, deployments, and experimentation cycles)
About the Role
At Pavago , one of our clients is hiring a Full-Stack AI Engineer to design, build, and deploy production-ready AI applications that combine modern software engineering with applied artificial intelligence.
This is a highly technical, hands-on role where you’ll build intelligent products from end to end—integrating Large Language Models (LLMs), machine learning models, vector databases, cloud infrastructure, and modern web applications into scalable production systems.
You’ll collaborate closely with product managers, data scientists, and engineering teams to develop AI-powered solutions that automate workflows, improve user experiences, and create measurable business impact.
If you’re passionate about shipping AI products—not just experimenting with models—this role is built for you.
What You’ll Own
AI Application Development
- Build and deploy AI-powered applications using modern software engineering best practices.
- Integrate LLMs and machine learning models into production environments.
- Develop intelligent features including:
- AI chatbots
- Semantic search
- Document intelligence
- AI copilots
- Workflow automation
- Build scalable APIs that expose AI capabilities to applications.
LLMs, RAG & AI Integration
- Integrate models using:
- OpenAI
- Hugging Face
- PyTorch
- TensorFlow
- Build Retrieval-Augmented Generation (RAG) pipelines.
- Implement semantic search using vector databases including:
- Pinecone
- Weaviate
- FAISS
- ChromaDB
- Optimize prompt engineering and inference workflows.
- Monitor model accuracy, latency, and production performance.
Data Engineering & AI Pipelines
- Build ETL pipelines for structured and unstructured data.
- Automate:
- Data ingestion
- Cleaning
- Validation
- Versioning
- Manage workflows using:
- Airflow
- Prefect
- Dagster
- Work with cloud data warehouses including:
- BigQuery
- Snowflake
- Amazon Redshift
- Optimize pipelines for scalability and cost efficiency.
Full-Stack Development
- Build modern user interfaces using:
- React
- Next.js
- Vue.js
- Develop scalable backend services using:
- Python
- FastAPI
- Flask
- Node.js
- Build APIs that support high-performance AI workloads.
- Ensure applications remain responsive, secure, and production-ready.
Infrastructure, DevOps & MLOps
- Deploy applications using:
- Docker
- Kubernetes
- Build CI/CD pipelines for both applications and AI models.
- Monitor infrastructure using:
- MLflow
- Weights & Biases
- Datadog
- Prometheus
- Improve:
- Inference latency
- Infrastructure reliability
- Deployment automation
- Cloud cost optimization
Security & Compliance
- Build secure AI systems using modern authentication and authorization practices.
- Protect sensitive business and customer data.
- Support compliance with:
- GDPR
- HIPAA
- SOC 2
- Implement API security, rate limiting, and access controls.
Requirements
Must-Have Qualifications
Experience
- 3+ years of software engineering experience with exposure to AI/ML systems.
- Experience building production AI applications.
- Experience deploying machine learning models into production environments.
Core Skills
- Strong proficiency in:
- Python
- JavaScript / TypeScript
- Hands-on experience with:
- OpenAI APIs
- Hugging Face
- PyTorch
- TensorFlow
- Experience building scalable REST APIs.
- Front-end development experience with:
- React
- Next.js
- Vue.js
- Strong SQL skills and experience working with cloud databases.
- Experience using:
- Docker
- Kubernetes
- CI/CD pipelines
- Familiarity with vector databases and AI inference services.
Nice to Have
- Experience building AI-powered S