Alpha Signal, LLC Backend Engineer Remote · Full time Company website

Apply for Backend Engineer

AlphaSignal is building the intelligence layer for AI - a real-time, machine-readable map of everything happening in the field, linked into a single knowledge graph. We run the first real-time AI ranking system and the first autonomous editorial system in the world. Our newsletter reaches 300,000+ subscribers, making it the most-read independent AI publication on the internet.

About AlphaSignal

AlphaSignal is building the intelligence layer for AI engineers and developers. We run a real-time platform that ranks the most important updates in AI — new research papers, model updates/benchmarks, trending GitHub repos, and industry news — and break down why it matters to engineers and developers. We're one of the first, if not the first, real-time autonomous editorial platforms in the world. Our newsletter reaches 300,000+ subscribers, making it one of the largest technical AI newsletters for developers and engineers.

THE ROLE

You'll own the pipeline behind the platform: scrapers, an LLM enrichment and editorial layer, a MongoDB data layer, a ranking system that decides what matters, and the foundations of our knowledge graph. When throughput drops or something breaks, you diagnose it, ship the fix, and verify the recovery.

────────────────────────────────────────

WHAT WE'RE LOOKING FOR

3+ years of backend engineering with production ownership of a non-trivial system.

Python at a professional level — backend services, ML models, algorithms, and production-grade scripting.

Deep LLM fluency across providers (Claude, GPT, Gemini) — shipped production features, fluent with prompting, structured output, cost optimization, and failure modes.

Database depth — MongoDB, Postgres at scale, or comparable; indexes, query plans, atomicity, replication.

ML / vector search — recommendation systems, knowledge graphs, entity linking, and the full vector DB landscape (Pinecone, Weaviate, Qdrant, Milvus, pgvector, Chroma, FAISS, plus Atlas/Elasticsearch/OpenSearch).

Designed systems for large, growing traffic — caching, batching, async, and index tuning.

AWS / infrastructure — comfortable deploying and operating services on EC2 and the broader Amazon suite.

Fluent with modern AI dev tooling (Cursor and similar).

Solid engineering practices: observability, monitoring, and keeping a codebase healthy as it scales.

────────────────────────────────────────

BONUS POINTS

Experience at a high-traffic content platform (Medium, Substack, Reddit, etc.).

Familiarity with arXiv, GitHub, Hugging Face, or X APIs.

Content systems: feeds, aggregators, recommenders.

Scraping at scale, deeper prompt engineering, or early-stage startup experience.

────────────────────────────────────────

TECH STACK

Python 3.11+, MongoDB Atlas (incl. vector search), Pinecone / Weaviate / Qdrant / Milvus / pgvector / Chroma / FAISS, LLM APIs (Claude, GPT, Gemini), AWS (EC2 + broader suite), Firecrawl, BeautifulSoup, arXiv / GitHub / Hugging Face / X, Cursor, Sentry, cron-scheduled services.

Non-negotiables: Python, LLM fluency, database depth, AWS/infra comfort.

────────────────────────────────────────

WHAT YOU'LL GET

Full ownership of a critical, high-impact system.

Direct work with the founder.

Competitive compensation ($125,000–$150,000).

Remote, async-first, low-meeting culture.

Four weeks PTO 

Healthcare, dental and vision covered 80%