Software Engineer Intern

ProNexus
Remote

About The Position

We’re building ProNexus: the all-in-one platform for sourcing human intelligence with AI. Consulting and research teams rely on human experts for primary research—finding them, vetting them, scheduling them, capturing insights, and turning those insights into reusable knowledge. Today that work is fragmented across inboxes, spreadsheets, CRMs, and manual workflows. ProNexus brings it all together: AI-powered sourcing + outreach workflows + expert/CRM management + project execution + an “org memory layer” where insights compound over time instead of getting lost in decks and docs. Right now it’s two founders. We’re looking for a Gen AI/Backend Software Engineer Intern (Python) who wants to ship production code, learn fast, and take real ownership—without “intern busywork.”

Requirements

  • Strong Python fundamentals (clean code, typing hygiene, debugging ability).
  • Comfortable with HTTP APIs, JSON, auth patterns, and database-backed systems.
  • Strong interest in GenAI / prompt engineering, with experience building LLM-powered features (projects are totally fine).
  • Some experience shipping something real (project, internship, open source, production app).

Nice To Haves

  • You’ve built backend systems in Python and want to go deeper.
  • You’re excited about GenAI + agent workflows and can write strong prompts / schemas to get reliable outputs.
  • You like building one-off AI agents for specific workflows (extract → classify → enrich → route) and iterating until they’re dependable.
  • You ship fast, unblock yourself, and don’t need hand-holding to make progress.
  • You enjoy a tight feedback loop with founders and real users.
  • Can contribute to React / Next.js + TypeScript frontend development.

Responsibilities

  • Build and ship backend features end-to-end (API → DB → integrations).
  • Implement and improve FastAPI endpoints, background jobs, and core services.
  • Work with Postgres (Supabase): schema changes, queries, performance, data integrity.
  • Integrate external systems (e.g., enrichment providers, outreach tooling, internal workflows).
  • Help us build one-off AI agents that automate internal + customer workflows (e.g., sourcing support, enrichment, summarization, extraction, classification, routing).
  • Write and iterate on prompts, few-shot examples, and structured outputs (JSON schemas) to make agent behavior consistent.
  • Improve agent quality with lightweight evals: small test sets, edge cases, regression checks, and prompt/version tracking.
  • Add tests, logging, and basic observability so we can move fast without breaking things.
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