HN Who's Hiring💵 paid workby dralexmacscored by google/gemini-2.5-flash

Northstar Security | Software Engineer | SF Bay Area | Onsite | Full-time We're a seed-stage startup building the contex

Visit project ↗Discussion ↗

💵 Funded work— see “Deliver it” below for how to respond.

Opportunity

AI-buildable

Traction

Creativity

The take

effort: ~3+ months

This is a job posting for a full-time, onsite software engineer at a seed-stage startup called Northstar Security. They are building a 'context layer for agentic cybersecurity'. The role is in the SF Bay Area.

Demand & gap

Painkillerdemand 69

Demand

Will. to pay

Gap

Buyer

Enterprise / orgs

The gap in what exists: Existing security tools often lack deep contextual understanding for autonomous agentic responses, leading to alert fatigue or delayed responses; a dedicated context layer could improve precision.
Wedge to win: Target security operations centers (SOCs) in mid-market or enterprise companies struggling with manual triage and wanting more autonomous, context-aware threat detection and response.
Reputation value (worth doing free for proof) — 70/100: Contributing to or building an early-stage product in agentic cybersecurity demonstrates cutting-edge AI engineering and security domain expertise, valuable for future B2B AI/security offerings.
Likely monetization: B2B SaaS subscription (per agent/per data volume)
Incumbents to beat: SentinelOneCrowdStrikePalo Alto Networks

Deliver it

A starter prompt for Claude Code, what you'll need, and how to reach them.

You are a senior software engineer working on a seed-stage startup building a 'context layer for agentic cybersecurity'. Your goal is to develop a proof-of-concept (PoC) system using Next.js 16 App Router, React 19, Tailwind v4 for the frontend, and a Node.js/Python backend with Neon Postgres on Vercel for data storage. The PoC should demonstrate the ability to ingest security events (e.g., simulated log data, network alerts), enrich them with contextual information (e.g., user identity, asset criticality, threat intelligence lookups), and expose this context via an API for a hypothetical 'agentic' system. Focus on creating a data model for context, an ingestion pipeline for event data, and an API endpoint to query contextualized events. Deliver: a working PoC application that can receive simulated security events via a simple API, store them with added context in the Postgres database, and display a web interface showing these enriched events and allowing basic filtering. Implement a 'verify' step by adding a test that ingests a sample event, queries it, and asserts that the expected context has been added.

Prerequisites — cost & what to learn

Vercel account with a linked GitHub repository

How you'd build it

1Research existing agentic cybersecurity solutions and their limitations regarding context understanding.
2Develop a prototype 'context layer' that can ingest security event data from various sources (logs, network traffic, endpoint data).
3Implement initial agentic capabilities that leverage this context to detect anomalies or respond to threats (e.g., using LLMs for reasoning).
4Design and build a user interface for security analysts to interact with the context layer and agents.
5Focus on data integration and normalization for diverse security data sources.

Risks & moats

Building a robust and accurate 'context layer' for cybersecurity is complex and requires deep domain expertise.
Agentic cybersecurity is an emerging field with significant R&D challenges and potential for false positives/negatives.
Competitors include established security vendors and other well-funded startups in the AI/cybersecurity space.
This is an onsite, full-time role; the operator is a solo founder, which is not a direct fit for taking this specific job.

Original context

Northstar Security | Software Engineer | SF Bay Area | Onsite | Full-time We're a seed-stage startup building the context layer for agentic cybersecurity - if you're in the SF Bay Area reach out to alex@northstar.security