- Company Name
- TechTree
- Job Title
- Full-Stack AI Engineer
- Job Description
-
**Job Title:** Full-Stack AI Engineer
**Role Summary:**
Design, build, and scale AI‑agent infrastructure and AI‑powered product features across the full technology stack. Own end‑to‑end delivery of frontend interfaces, backend services, cloud deployment, and AI model integration for enterprise‑grade applications.
**Expectations:**
- 5+ years professional software engineering experience.
- Proven production use of React and Next.js.
- Strong backend development in Python (Django/FastAPI preferred).
- Hands‑on experience with cloud platforms (AWS, GCP, Azure), containerization, and CI/CD.
- Demonstrated ability to design, deploy, and monitor AI systems (RAG pipelines, multi‑agent orchestration, model fine‑tuning).
- Solid understanding of databases, caching, and task queue frameworks.
- Ability to mentor junior engineers and collaborate with cross‑functional teams.
**Key Responsibilities:**
- Develop and maintain responsive front‑end applications using React/Next.js.
- Build, test, and deploy robust Python‑based APIs and services (Django, FastAPI, or equivalents).
- Design and implement CI/CD pipelines, automated testing, and observability solutions.
- Plan, provision, and optimize cloud infrastructure (AWS/GCP/Azure) with Docker and Kubernetes.
- Create and maintain data pipelines for model training, evaluation, and continuous improvement.
- Integrate and scale Retrieval‑Augmented Generation (RAG) systems, multi‑agent frameworks, and LLM evaluation tools into production.
- Implement background workers and task queues (Celery, RQ) and use Redis for caching/pub‑sub.
- Ensure system scalability, performance, security, and reliability.
- Mentor junior developers and promote best engineering practices.
**Required Skills:**
- React, Next.js
- Python (Django, FastAPI)
- Relational & NoSQL databases
- Git & collaborative workflows
- Cloud services: AWS, GCP, Azure
- Docker, Kubernetes
- CI/CD pipeline tools
- Redis, Celery, RQ (or similar task queues)
- AI system development: RAG pipelines, multi‑agent orchestration, model fine‑tuning, performance monitoring, LLM evaluation techniques
- Problem‑solving and communication skills
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Software Engineering, or a related technical field (or equivalent professional experience).
- Preferred: Certifications in cloud platforms (AWS Certified Solutions Architect, Google Cloud Professional Engineer, Azure Administrator) or AI/ML (e.g., TensorFlow, PyTorch) – not mandatory.