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

Hacker News Discussion ↗

Hundreds of developers, designers, data scientists, SREs, product managers, and security specialists worldwide post brief profiles in this recurring Hacker News hiring thread, advertising their skills and availability. Most are seeking remote roles—often senior or founding-engineer level—in areas like AI/agents, backend and distributed systems, mobile and web apps, DevOps/platform engineering, and UX/product design. The thread serves as a talent directory for startups and established companies looking to hire experienced, often highly specialized, technologists on full‑time, contract, or fractional terms.

Overall focus of the thread

  • Monthly “who wants to be hired” thread with hundreds of people posting short self-profiles.
  • Dominated by software engineers, but also includes designers, product managers, security, data/ML, infra, and a few non-technical roles.
  • Most emphasize remote or remote-first work; relocation is usually conditional or limited to specific regions.

Technical specializations

  • Strong presence of:
    • Backend / systems: Go, Rust, Python, Java, C#, Node.js, JVM, .NET, microservices, high‑throughput and low‑latency systems.
    • Web / full‑stack: TypeScript, React/Next.js, Vue, Angular, Ruby on Rails, Django, Laravel, PostgreSQL, Redis.
    • Mobile / client: iOS (Swift/SwiftUI), Android/Kotlin, React Native, Flutter, macOS, some desktop (Electron, Qt, JUCE).
    • DevOps / platform / SRE: Kubernetes, Terraform, AWS/GCP/Azure, observability stacks, CI/CD, cost optimization.
    • Data / ML / MLOps: Spark/Flink, data warehouses, ETL/ELT, analytics infra.

AI and agentic systems

  • Large subset explicitly markets:
    • LLM integration, RAG pipelines, vector databases, evaluation harnesses.
    • Multi‑agent / “agentic” systems using LangGraph, LangChain, CrewAI, MCP, custom runtimes.
    • Applied AI in domains like search, developer tools, document processing, observability, and automation.
  • Several candidates highlight building full AI products (not just demos): latency, reliability, guardrails, evaluation, and cost control are recurring themes.

Product, design, and leadership

  • Multiple senior product designers, design engineers, and UX/UI specialists comfortable working “design-to-code”.
  • Product managers and “AI‑native” PMs who prototype and implement 60–80% of products themselves before handoff.
  • Engineering managers, CTOs, fractional CTOs, staff/principal engineers, and strategy/architecture advisors position themselves for leadership or advisory roles.

Engagement models

  • Many explicitly seek:
    • Contract, fractional, or consulting work (often with well‑defined rates or B2B setups).
    • Early‑stage / founding‑engineer roles with high ownership.
    • Short scoped sprints (e.g., performance tuning, infra migration, app rescue).

Privacy, scraping, and LLM-era concerns

  • A short meta discussion questions posting resumes and detailed profiles publicly in “the age of LLMs and data scraping”.
  • One commenter notes this is effectively a high‑quality dataset of wealthy targets; another replies these threads have existed for years and participants want to be found.
  • Separate comment wonders why resumes are still needed if one can just “write a very detailed prompt to AI,” implying shifting norms around hiring materials.