stackchain/troupe-standup
2
0 Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity
Files
b04ebe0960eead9d3f5ad0c7a4266cb7471cde33
troupe-standup/career-lane/apply-queue-2026-10-13.md
T

11 KiB
Raw Blame History

APPLY QUEUE — 2026-10-13 (for Timmy to queue, Alexander submits)

Authority: Alexander asked Zeph to send Timmy "everything I can apply for today" and have Timmy queue it for Alexander's own submission. Rules: Timmy queues only — never submits, never creates accounts, never contacts anyone on Alexander's behalf. Materials below are public-safe (professional name only; no email, phone, or private facts). Compiled by Zephyrus Sparkborn, 2026-10-13 ~13:35Z. Liveness verified from a clean external network unless marked otherwise.

Queue order (by conversion speed)

1. Turing — "Senior Python Engineer - AI Agents Evaluation" ✅ APPLY-READY

  • URL: https://work.turing.com/r/HI7GzvKjPF (200/43,820 B, surfaced <24h, verified 2026-10-13)
  • Terms: full-time contractual, remote, 40h/wk global overlap, 1-month, ~25min AI interview.
  • Pay: UNVERIFIED (none stated on page).
  • Friction: LOW — Alexander already has a Turing account (Oct-3 interview).
  • Materials: adapt the item-2 pitch below (same skill family).
  • Missing from Alexander: rate number if the form asks.

2. Turing — "Senior SWE – Python (LLM Evaluation & Repository Validation)" ⚠️ GATED

  • URL: https://work.turing.com/r/C94ooVlx1g (200/49,847 B, verified live 2026-10-13 ~09:28 ET and re-verified by Zeph ~13:30Z)
  • Terms: contractor (no benefits), ≥4h/day, min 20h/wk, 4h PST overlap, duration 4–8 weeks (not 3 months — corrected 2026-10-13), expected start next week. Evaluation: profile/delivery review + 45–60 min delivery interview.
  • Pay: UNVERIFIED (none stated on page).
  • Gates on the live listing (verbatim, lines 47–49): "Bachelor's or Master's degree in Computer Science or a related technical discipline" and "Minimum 8 years of hands-on software engineering experience in leading product companies or technology startups." Whether either is a hard filter is UNVERIFIED. Alexander's pitch narrative runs ~7 years; flag candidly, his call.
  • Geo: no geographic-eligibility copy on the page. A same-title sibling posting (pLkv7ld46e) was killed 2026-10-13 for non-US locations (India/Pakistan/Nigeria) — surviving posting implies US fine; Alexander is a US citizen. Eligibility risk LOW, not proven.
  • Friction: LOW (Turing account exists).
  • Materials: paste-ready pitch DONE (below). Screening answers DONE (below).
  • Missing from Alexander: (a) go/no-go given the gates; (b) rate number if the form asks (Oct-1 Turing inbound was $100–150/hr — his call, do not invent).

Pitch (paste-ready, ~120 words, his voice):

I'm Alexander Payne, a senior backend engineer (Python) working as an independent contractor. For the last two years my day job has been directing and evaluating AI coding agents end to end on real repositories: setting acceptance criteria, reviewing agent behavior and tool use at the diff level, and making release decisions on their output. Underneath that, 5+ years of production Python — Django, Flask, REST APIs, PostgreSQL, Docker, CI/CD — so I judge generated and human code the way someone who has shipped it does: by running it, reading the tests, and checking coverage, not by skimming the output.

Recent work includes line-level audits of public codebases (a 121-entry ledger audit where every outbound source was fetched and tested, and a 30-entry clause-grading sweep with 129 verified rows). I'm comfortable cloning an unfamiliar repo, Dockerizing it, getting its suite green, and saying exactly where the tests are thin. Remote, US citizen, available to start immediately, fine with PST overlap.

Screening answers (first passes — his words to confirm):

  • Why this role: "The role's core loop — triage real GitHub issues, stand up repos with Docker, evaluate unit-test coverage and quality, then run modified codebases locally to see how an LLM handles bug-fixing — is what I've done for two years evaluating AI coding agents, plus five years of production Python before that."
  • Python/Docker: "5+ years production Python (Django, Flask, REST, PostgreSQL); Docker and CI/CD are standard in my workflow — containerizing unfamiliar repos and getting their test suites running is routine. I navigate large unfamiliar codebases by reading tests first, then tracing call paths from failing or thin-covered areas."
  • LLM evaluation: "Two years directing and evaluating AI coding agents end to end: defining acceptance criteria, reviewing agent behavior and tool use, grading outputs against rubrics, and making release decisions. I run my own AI lab, so evaluating model output on real code is the day job."
  • Team-lead angle: "I've scoped and directed agent-assisted engineering work end to end — goals, constraints, acceptance criteria, release calls — which is the same shape as leading a small team against a quality bar."
  • Availability/auth: "Available to start immediately. US citizen, authorized to work in the US, no sponsorship needed now or in the future. 20 hrs/wk with PST overlap works."
  • Rate: [ALEXANDER'S NUMBER — do not invent.]

Honesty ledger (what this draft does NOT claim): no invented OSS contributions or repo names; the "public codebase audit" lines describe his real Stackchain archive/forge audit work (evaluation, not authorship); no Go/Rust/React/AWS/K8s claims; no degree claim; no Staff-scope claim; no invented pay expectation.

Direct-lane door (Alexander sends himself — Timmy does not): Jonathan Siddharth, co-founder & CEO, Turing (X: @jonsidd — handle from public podcast description, NOT live-confirmed in-app; verify @jonsidd inside the app before sending):

Hi Jonathan — I'm Alexander Payne, a senior backend engineer (Python) contracting independently. For two years my day job has been directing and evaluating AI coding agents end to end on real repos — acceptance criteria, diff-level behavior review, release decisions on their output — on top of 5+ years of production Python. Your LLM Evaluation & Repository Validation posting (benchmark tasks, utility + safety evaluators, reference solutions) is squarely what I do. Happy to share background or run your eval process — available to start next week. — Alexander

3. Turing — "Senior SWE – LLM Evaluation (US/Canada/WEU based)"

  • URL: https://work.turing.com/r/alSSk0vX2k (200/46,602 B, verified 2026-10-13; watch→verified upgrade from 10-12, not a duplicate)
  • Terms: part-time contractor, remote, 1 month + extensions.
  • Pay: UNVERIFIED.
  • Friction: LOW (Turing account exists).
  • Materials: adapt item-2 pitch.

4. OpenTrain — "Agentic AI Software Engineer"

  • URL: https://www.opentrain.ai/jobs/agentic-ai-software-engineer--cmv0u6ybv000m06i05anl5nt2/ (200/193,284 B, Apply-now CTA, verified 2026-10-13)
  • Terms: contract part-time, remote worldwide, 20+ h/wk, posted Oct 9; MCP tools, AI coding-assistant workflows.
  • Pay: UNVERIFIED. Entry-tier watch flag (experience-tier badge below senior on 2026-10-10 review) — flagged, not disqualified.
  • Flow: OpenTrain board application (account creation expected; same board family as item 7).

5. OpenTrain — "Secure Coding-Agent Benchmark Engineer"

6. micro1 — "Senior Software Engineer" $245–280/hr (second door)

  • URL: https://jobs.micro1.ai/post/3d79ba82-926b-48c0-9d15-8791a364ea81 (verified LIVE 2026-10-12 ~09:30 ET, logged-out guest browser)
  • Terms: remote, contractor, AI code evaluation / model review (evaluate AI-generated code; write coding problems, reference solutions, test cases; review model reasoning). Board card: "Senior Software Engineer", $245–280/hr, Remote, Contractor, board date Aug 27 2026.
  • Pay: $245–280/hr (board-stated).
  • Flow: "Apply now" → email then Continue, or Continue with Google / LinkedIn; creates a candidate account ("talent dashboard"). Screening per their own words: "Take the AI interview" (Apply → AI interview → onboarded → start earning), plus skill-based assessments and certification. No proctored desktop-sharing/monitoring software mentioned on the pages checked.
  • Friction: MEDIUM — new account + heavier screening than OpenTrain.
  • Needs Alexander's authorization before any application is started (new auth — do not submit without it).
  • Uncertainties: minor title mismatch (card shows "Senior Software Engineer", not the longer mirror title); "~100 openings" mirror claim unverifiable; the Oct-4 desktop-sharing red flag was a DIFFERENT micro1 role (Code Generation Research Engineer $50–100/hr), not this listing.
  • LinkedIn hard rule: OAuth on LinkedIn's own page is fine; never type a LinkedIn password into a third-party form.

7. OpenTrain — "Senior Software Engineer – Remote" $245–280/hr ⚠️ EXPIRING

  • URL: https://www.opentrain.ai/jobs/software-engineering-ai-code-evaluator--cmtc1224000320ajcwfjzt792/
  • Terms: remote contractor, AI code evaluation.
  • Pay: $245–280/hr (board-stated).
  • Status 2026-10-13: DELISTED from employer boards. Canonical page still serves 200 but is orphaned — treat as expiring. Item 6 (micro1) is the live door to the same project family.
  • Application flow is PARKED at Cloudflare "verify you are human" checkbox (nothing submitted, no account created). Alexander authorized "Submit for me" 2026-10-10; the checkbox choice is still his.

Carry (not re-verified this morning — confirm liveness before queueing)

8. Vettedlance — "Senior SWE, Agentic Coding Evaluation"

9. AuraOne — "AI/ML Engineer, Internal Platforms"

What Timmy should do with this

  1. Order the queue as above; mark per-item status: READY (1, 3 — adapt pitch; 2 — pitch done) / NEEDS-ALEXANDER (2: go/no-go + rate; 6: apply authorization; 7: checkbox decision — expiring) / DRAFT-NEEDED (3, 4, 5: role-specific pitch from item-2 materials).
  2. Draft role-specific pitches for items 3, 4, 5 from the item-2 materials + honesty ledger; post drafts back to the pipe for Alexander's approval — never final.
  3. Track Alexander's answers (rate number, go/no-go, authorizations) as they come in; update statuses.
  4. Do NOT submit, create accounts, or contact anyone.

Standing rules (unchanged)

  • Free-tier evaluation only — never pay a vendor (Alexander, 2026-10-06).
  • Truthful, resume-grounded answers only; never invent experience, rates, degrees, employers, or other facts.
  • Never type a LinkedIn password into a third-party site (Terac rule).
  • Contact details stay off the public pipe.
Reference in new issue View Git Blame Copy Permalink