Full Stack Engineer

DAEMO AMERICA INC.
San Francisco, CA, United States
about 2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$90,000.0 - $170,000.0
Working hours
Regular working hours
Job source

Tech stack

Secure Shell (SSH) Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Amazon Elastic Compute Cloud Amazon S3 Bash Shell BigQuery Encodings Continuous Integration Cron Data Deduplication
+26 more
Web Scraping Extract Transform Load (ETL) Linux Domain Name System (DNS) Github Python (Programming Language) MongoDB Node.Js Next.js Search Technologies SQL Databases Data Streaming TypeScript Network Routers Tailwind ReactJS Large Language Models Caching Backend Low Latency Playwright Google Bigquery Cloudflare Front End Software Development Data Pipelines Docker

Requirements

Languages

TypeScript (Expert) - all production frontend/backend code

Python (Proficient) - pipelines, scraping, LLM orchestration

SQL / MongoDB (Proficient) - BigQuery ingestion, aggregation pipelines

Bash/Shell - EC2 ops, cron, deployment scripts

Frameworks & Infrastructure

Next.js (App Router), React, Tailwind CSS / shadcn/ui, NextAuth.js

Node.js + Server Actions , OpenAI-compatible API (streaming, tool calling)

MongoDB Atlas - document modeling, Atlas Search

Docker / Docker Compose - all services containerized

Linux / tmux - SSH, process management, EC2 service administration

Engineering Capabilities

Full stack ownership: data model * API * UI * deploy (no tier handoff)

Async/concurrent systems & data pipeline architecture (ETL/ELT, deduplication)

Web scraping at scale - anti-bot evasion, government/political sources Playwright,BeautifulSoup), Rust - Core system runs on Rust

AWS Bedrock - Claude 3.x families; cost/quality/latency tradeoffs AWS (EC2, S3), Cloudflare (DNS, tunnels), CI/CD (GitHub Actions)

Google BigQuery - large-scale parallel data ingestionRedis - caching, job queuing, pub/sub

Signal CLI - secure messaging integration on Linux EC2

Multi-provider LLM routing (Fireworks AI or similar)

Embedding + vector search (Voyage AI or equivalent)

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