Description:
About The Role
If you're the kind of engineer who gets excited about building AI systems that actually work in production — not just demos — this might be the role for you.
We're growing our team and looking for a Senior Full Stack AI Engineer who can move across the full stack with confidence: from crafting clean, responsive frontends to architecting backend systems that scale, to wiring together LLMs, vector databases, and inference pipelines that power real products used by real people.
This isn't a role where you'll be handed a neat spec and told to execute. You'll help shape the architecture, make meaningful technical decisions, and work with people who care deeply about doing things right.
Role Details
- Experience: 5+ years in professional software engineering
- Employment: Full-Time
- Location: Remote-first
- Focus: AI/LLM systems, Full Stack development, Cloud infrastructure
What You'll Be Working On
Day to day, you'll be involved in a mix of the following:
- Designing and building scalable AI-powered web applications, end to end
- Creating clean, fast frontends with React.js and Next.js
- Writing solid backend services and APIs with FastAPI — built for performance and reliability
- Building RAG pipelines, AI agents, and LLM orchestration systems that work at scale
- Architecting semantic search and vector retrieval systems that return meaningful results
- Setting up distributed, event-driven systems with proper queue and caching layers
- Deploying and managing cloud infrastructure, including GPU workloads for AI inference
- Profiling and optimizing systems for speed, cost, and resilience
- Contributing to architectural decisions and helping the team level up technically
What We're Looking For
We care more about what you can do than how perfectly your resume matches a checklist. That said, here are the areas where you'll need to be genuinely strong:
Frontend
- React.js
- Next.js
- TypeScript
- Tailwind CSS
- Redux / Zustand
- Server-Side Rendering (SSR)
- Static Site Generation (SSG)
- WebSocket Integration
- Performance Optimization
- CDN & Asset Delivery
Backend & Systems
- Python & FastAPI
- RESTful APIs
- Async Programming
- Microservices
- PostgreSQL / MongoDB
- Redis
- RabbitMQ / Kafka
- Celery / BullMQ
- Event-Driven Architecture
- Distributed Systems
- API Gateway Design
- Auth & RBAC
AI & LLM Engineering
- LangChain / LangGraph
- LlamaIndex
- RAG Pipelines
- Prompt Engineering
- AI Agent Frameworks
- Embeddings & Semantic Search
- Streaming LLM Integrations
- Context & Memory Management
- OpenAI / Claude / Llama
- Mistral / Gemini / Open-Source LLMs
Model Fine-Tuning & Inference
- Hugging Face Transformers
- LoRA / QLoRA / PEFT
- Model Quantization
- GPU Inference Optimization
- vLLM / Ollama / TGI
- Batch Inference Pipelines
- CUDA Fundamentals
Vector Databases
- Pinecone
- Weaviate
- Qdrant
- ChromaDB
- FAISS
- Milvus
Cloud, Infrastructure & DevOps
- Docker & Kubernetes
- AWS / GCP / Azure
- CI/CD Pipelines
- Nginx & Linux Admin
- GPU Infrastructure
- Cloudflare / CloudFront
- S3 / GCS Object Storage
- Prometheus / Grafana
- ELK Stack
- Terraform / Ansible
Nice To Have (But Not Required)
These aren't dealbreakers, but they'll definitely get our attention:
- Experience with OCR, Computer Vision, or multimodal AI
- Hands-on work with YOLO or real-time inference systems
- Background in high-concurrency or real-time platforms
- Familiarity with web scraping, document extraction, or data ingestion pipelines
- Experience running AI infrastructure at enterprise scale
