Full-Stack AI Engineer

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.