Full-Stack AI Engineer at Pavago

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.

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.