Why This Job is Featured on The SaaS Jobs

This Full Stack and Backend Engineer role sits at a clear intersection of modern SaaS patterns and AI product delivery. The listing points to an early stage, paying, VC backed company building an intelligence platform for mid market and enterprise customers, which typically means strong emphasis on reliability, multi tenancy, and secure data handling alongside rapid product iteration. The scope spans real time data pipelines, LLM summarization, and a customer facing portal, reflecting how many SaaS products are now blending workflow software with AI driven outputs.

From a SaaS career perspective, the role offers end to end exposure that is hard to replicate in more segmented engineering orgs. Owning the path from data model and ingestion through APIs, UI, and deployment builds fluency in the full product surface area, including observability and production debugging across multi stage systems. Experience with tenant isolation, access control, and audit logging is broadly transferable across B2B SaaS, especially as platforms expand into regulated or enterprise environments.

This position is best suited to an engineer who prefers high ownership, enjoys switching between infrastructure, application logic, and frontend delivery, and is comfortable making pragmatic tradeoffs in evolving systems. It will fit someone who wants hands on work with LLM integration and evaluation while still grounding product behavior in dependable data pipelines and operational discipline.

The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.

Job Description

Full Stack Engineer — Daemo AI

Full-Time · San Francisco, CA · In-person preferred, hybrid/remote possible

~ $100k-200k/yr

APPLY: https://airtable.com/app16PZxY2eVBKHL0/pagLyUbKm36xxcn8D/form

About the Role

Daemo AI is an intelligence platform catering to middle-market and enterprise clients. This engineer owns the full stack — from real-time data pipelines and LLM summarization engines to the user-facing web portal.

Required Skills 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
Rust — systems on Rust

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)
Real-time streaming — SSE/WebSockets for agent responses
Production debugging across multi-stage pipelines
Multi-tenant security — data isolation, access control, audit logging

AI / LLM

LLM API integration — chat completions, tool/function calling, streaming, context management
Prompt engineering for summarization, personas, research agents
Agent architecture — multi-step tool use, memory patterns, RAG
AI output evaluation — hallucination detection, guardrails

Preferred Skills

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 ingestion
Redis — 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)
Automated briefing pipelines — scheduled ingest → summarize → deliver

About Us

SF-based early-stage AI startup. Yale Engineering founding team. Paying clients. VC-backed. Growing & hiring.

Website: https://www.daemo.ai/
LinkedIn: https://www.linkedin.com/company/daemo-ai/
APPLY: https://airtable.com/app16PZxY2eVBKHL0/pagLyUbKm36xxcn8D/form

Daemo AI

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