Ask HN: Who wants to be hired? (August 2026)

  Location: Europe, Role Type: Fractional, Remote / Worldwide
  Remote: Yes
  Willing to relocate: Yes
  Technologies: Kafka, Flink, Spark, Cassandra, Scala, Rust / PyO3 / Tokio, Python, Zookeeper, Databricks, Delta Lake, BigQuery, Redshift, Hive, Kinesis, Airbyte, Airflow, Temporal, DBT, Aerospike, Snowflake, PrestoSQL, Trino, Clickhouse, SQL, Vector DBs, Golang, gRPC/protobuf, Terraform, CUDA
  Resume: https://drive.google.com/file/d/1lZuSpneLDVzzYoeaA8or-m5m2dfYAMB4/view
  Email: in the profile (please do mention "Via HN" in the subject for your email to land in the right place in my inbox)

Core Focus Areas:

● Cassandra (Data Modeling, Troubleshooting Performance And Operational Issues)

● Apache Iceberg (Scaling, Tuning, Self-Hosted Setup)

● Stream Processing At Scale: Kafka, Flink, Spark Streaming, Storm

● Custom-Crafted Contextualized Embeddings, Vector-Based Semantic Search, Deep Intent Recognition In Search Engine Queries

● Languages: Scala, Rust, Python, SQL (proficient), Golang (ramping up)

Educational Background: Computer Science.

Solid experience working remotely and working with teams that are distributed geographically. I typically work Pacific Time hours.

Ask: $385K base, pro-rated.

Remote: Yes

Willing to relocate: For the right opportunity

Technologies: HubSpot, Pipedrive, Zoho CRM, GA4, LinkedIn Campaign Manager, Zapier, UTM and attribution setup, dashboards, campaign QA, A/B testing

Résumé/CV: https://drive.google.com/file/d/1Ip4uzZrIdsDe5pTae1c79M__Pm1...

Portfolio: https://kurt.pascuals.org

Email: kurpeetologist@gmail.com

I’m looking for Growth, GTM, or Marketing Operations roles at an early-stage or technical company. I’m strongest at building the machinery behind growth: campaign systems, tracking, launch processes, dashboards, and workflows that make marketing faster, more consistent, and easier to measure. At NXT-USA, I created reusable campaign templates, naming and UTM standards, QA processes, lead-gen workflows, and reporting systems, then used that foundation to help a technical B2B campaign generate 50+ qualified leads on a limited budget.

I also built WealthOS, a personal finance app, because I wanted to understand product and user experience beyond the marketing layer. I have a master’s degree in Entrepreneurship and Innovation. I’m looking for a team that needs someone who can bring structure to messy growth problems while staying close enough to the work to launch, test, and improve it.

Remote: Yes

Willing to relocate: Yes

Technologies: Typescript/Javascript, Node.js, React, Python, Postgres, AWS, Docker, Terraform, Kubernetes, Godot, Rust

Resume/CV: https://camerong.com/docs/resume%20-%20cameron%20guthrie.pdf

LinkedIn: https://www.linkedin.com/in/cameron-guthrie-8340032a/

Email: camerongu3@gmail.com

Full-stack software engineer, good at turning domain knowledge into software, learning new systems, and building apps people actually enjoy using.

At my last job I led a team and helped build a Windows desktop app that pulled data from native node modules and added overlays to games. I used Electron, Node, Typescript, React, and Redux to build it, AWS for CI/deployments, and finally TrackJS and Sentry for logging/monitoring. I also started learning Rust from working with other engineers on the native node modules.

AI engineer, ~2 years on production RAG and agent systems. Contract or full-time.

I make retrieval measurable. Most RAG that "feels wrong" has no eval set, so nobody can say whether the fault is chunking, embeddings, reranking or the prompt. I build the eval set from your corpus first, then fix what the numbers point at.

Recent: rebuilt Qdrant retrieval with clause-aware chunking and cross-encoder reranking. Precision ~55% to 95%+ on their internal evaluation dataset, across 500+ queries. Cut manual review ~60% with LangGraph workflows using conditional routing and human-in-the-loop gates.

Chunking writeup on the site: fixed-width severed 57% of clauses in the test corpus, clause-aware kept 99.1% intact.

OSS: MCPHub (MCP server testing harness, JSON-RPC inspector, P50/P95/P99 latency) and AgentMesh (multi-agent orchestrator with approval gates).

4+ hrs US Eastern overlap, full CET.