[HIRING] OpenClaw + VPS person — paid trial task, ongoing work | Remote, any timezone

Jobs
21

  1. I’d have the Telegram agent receive the photo together with a job identifier (job number, QR code, production ID, or job context). An n8n workflow would download the image, store it in a structured location (S3-compatible storage, NAS, or cloud bucket), then update the corresponding monday.com item with the image URL and production status. If the identifier is missing, I’d add a validation step that prompts the user to select or confirm the correct job before the workflow continues. My goal would be to make the photo-to-job association fully deterministic so there’s no manual reconciliation later.

  2. Most relevant project:
    AI Assistant for a Real Estate Agency:
    https://drive.google.com/file/d/1Ol2fMO7QA2Chicx_UFkQL53Nzss8uwKk/view?usp=sharing

Portfolio:

  1. $500 fixed + $40–50/hour ongoing

  2. Timezone: Flexible overlap with Australia (available across multiple time zones).
    For urgent issues, I can typically respond within 1–3 hours during active hours and the same day for critical production incidents.

Your stack is exactly the type of work I enjoy—AI agents, self-hosted infrastructure, n8n orchestration, and building repeatable systems that can scale beyond a single production box. For the VPS trial I would not only deliver a hardened and documented OpenClaw host, but also provide clear reasoning behind every security and operational decision, a concise runbook, and a screen recording so the process can be replicated consistently across future deployments.

WhatsApp: +375293761570

22

You know the strongest part of your brief is that you care about the runbook and reasoning, not just “make the box work.” For the trial, I’d treat it like production from the start: pinned versions, dedicated non-sudo user, systemd, loopback defaults, env-file secrets, and a short handoff doc explaining every choice. That makes the next VPS repeatable instead of becoming another one-off server setup.

23

Hi James, I can take a paid trial like this.

For the Telegram photo flow: I’d let Telegram/n8n receive the photo event, store the image in private object storage or a restricted Drive folder, then write the stored file URL back to the matching monday.com job item. I would avoid matching only by free text; job id, QR/code, button context, or a small manual review queue is safer for ambiguous photos.

Relevant sample: GitHub - jordansilly77-stack/n8n-workflow-demo: Small n8n workflow demo for API checks and CRM handoff automation · GitHub

For the VPS trial I’d set up a non-root service user, SSH key-only login, UFW/fail2ban, OpenClaw under systemd, secrets in a restricted env file, and a short runbook with the important commands and rollback notes.

Fixed quote for the trial: $80. Ongoing: $15/hr. Timezone: China time, usually can check urgent issues within a few hours if I’m awake.

24

Hey James,

For the Telegram photo workflow: I’d have n8n receive the photo via Telegram webhook, then use the message caption or a preceding job ID prompt to identify the record. The photo gets uploaded to your storage (S3/Hetzner Object Storage) with a structured filename like
job_[ID]_[timestamp].jpg, then n8n updates the matching monday.com job row with the file URL and stores metadata (sender, timestamp, board ID). If no job ID is provided, the agent replies asking for it before storing — keeps the link deterministic, never guessed.

For the VPS hardening trial: pinned OpenClaw under systemd with dedicated non-sudo user, SSH key-only + UFW + fail2ban, CrowdSec for behavioural threat intel (better signal than fail2ban alone for repeat offenders across the network), Netdata for metrics, all services loopback-bound, secrets in 0600 env files, full runbook + Loom handover.

Let’s schedule a call to discuss the details further.

25

Question 1 — Photo to job record:

When the photo hits the Telegram bot, the n8n webhook fires and pulls the image file plus the message metadata (sender, caption, timestamp, chat ID). The caption — or a quick regex/Claude extraction step — gives you the job number; if the staff member doesn’t include one, you can prompt them inline via the bot before continuing. n8n then uploads the binary to your storage layer (S3-compatible object store, or even monday.com’s own file column via their API), gets back a URL, and writes that URL plus a timestamp and sender into the matching monday.com item — either by job number lookup or by matching the Telegram user to a board column. The whole chain is idempotent: if the upload or board write fails, n8n retries and the bot sends a Yes or No confirmation back to the staff member so nothing silently disappears.

2. Most relevant thing built: I dont have any to share.

3. Quote: AUD $400–600.

4. Timezone/availability: I can commit to a 2–4 hour response window during business hours, start from 8 PM UTTC+7.

note: CrowdSec + Netdata is a solid default for this use case. CrowdSec gives you collaborative threat intel and ban enforcement without the false-positive headaches of pure fail2ban alone; Netdata gives lightweight real-time metrics with almost no config overhead on a fresh Ubuntu box. The case for swapping either would only emerge if he already has a centralised observability stack (Grafana Cloud, Datadog) — in which case you’d feed into that instead of running Netdata standalone.

26

1. For the Telegram photo flow, I would require either a job id in the staff message/caption or a controlled job-selection prompt before storing anything. The Telegram message gives file_id, message_id, user, and timestamp; n8n should copy the photo to stable object storage under a path keyed by job id, then write the storage URL plus Telegram metadata back to the monday.com job record. If the match is ambiguous, I would route it to a human review queue instead of guessing, then send the staff member a confirmation only after the job record update succeeds.

2. Closest relevant proof of work style: https://paste.rs/SD2E4

3. Fixed quote for the trial: USD 300. Ongoing support/build rate: USD 35/hour. I would keep the trial bounded to the fresh throwaway VPS, documented hardening, install verification, runbook, and screen recording.

4. Timezone: UTC+7. For urgent issues I can usually acknowledge same day; if something is production-down, I would first ask for the exact failing surface, recent logs, and whether I am allowed to restart services before touching the box.

Transparent boundary: I am comfortable doing command-led VPS hardening with a written runbook and verification checklist, but I would not ask for live production secrets for the trial. I would prefer a fresh VPS, SSH key access, and permission to record the terminal work.

27

Hi — this is very close to the work I like doing: hardened VPS-hosted agent systems, n8n for deterministic workflows, and runbooks that someone can actually maintain later.

For the Telegram photo → job record flow, I’d keep Telegram ingestion as the trigger, then use n8n to fetch the file via Telegram API and store it in object storage or a private folder with a deterministic key like job_id/stage/timestamp. The important part is resolving the right job before storage: either parse a job code from the message/caption, map the staff chat/user + current active job, or ask the agent to confirm when confidence is low. Then I’d write the storage URL/file ID back to monday.com against the job record, log the event, and notify the staff member if the link failed or needed manual confirmation. I’d also keep retries/error alerts separate from the agent so missed photos don’t fail silently.

Relevant build: GitHub - Damika-Anupama/resume-jd-matcher: AI resume to job-description matcher: scores fit, extracts matched/missing skills and tailored suggestions. FastAPI + LLM (OpenRouter) backend, Next.js/TypeScript frontend, with an eval harness. Provider-agnostic with a deterministic mock mode. · GitHub plus my current Hermes/OpenClaw-style local agent-ops work; I can share the closest private runbook/architecture notes if useful.

Trial quote: USD 400 fixed for the hardened Hetzner/OpenClaw host + short runbook + screen recording. Ongoing: USD 45/hr, or we can package repeat VPS builds/maintenance into a monthly retainer once we know the load.

Timezone: Sri Lanka, UTC+5:30. I can usually respond same day and can schedule async handoffs with screen-recorded notes; for urgent break/fix I’d set a clear response window before we start.

28

Hi James,

  1. For the Telegram photo path: I would make the bot require a job context before accepting the finished-sign photo, either by active job selection, QR/job code, or the latest assigned job in the operator session. The bot stores the Telegram file_id plus a downloaded copy in the chosen storage, then n8n links the storage URL/hash back to the monday.com item/job record and writes a small audit row. If matching is uncertain, it should pause into a review queue instead of attaching the photo to the wrong job.

  2. Closest relevant link: SHAL Engineering Portfolio - S23 Ultra Proof, Backend, Android, AI API Rescue

  3. Fixed quote for the described throwaway VPS trial: USD 180. Ongoing work: USD 25/hr, or fixed slices when the scope is clear.

  4. Timezone: Europe/Moscow, UTC+3. For planned work I can usually respond same day; for urgent fixes I can normally jump in within a few hours when awake. The throwaway VPS + runbook + screen-recording workflow is a good fit for me.

29

On the photo question: the agent’s job is to turn a loose Telegram photo into a linked artifact with zero typing from the staffer. When it lands I’d take the file_id, pull the full-res file via getFile, and store the bytes in object storage (S3/R2/MinIO) under a deterministic key instead of leaving them in Telegram. The real work is linking it to the right job automatically, so I’d resolve the job from context: the sender’s current active job, a short job code in the caption, or a reply on the job’s own Telegram message, and if it’s genuinely ambiguous the agent asks one clarifying question rather than guessing. Then I write a row (job_id, storage_url, file hash, sender, stage, timestamp) to Postgres and update the monday.com item over the API, and I dedupe on the hash so a re-send doesn’t create a second record.

Quick context on me: I actually build on OpenClaw, I wrote and published the @fidacy/openclaw-plugin, and hardening self-hosted agent boxes is my daily work. I built Fidacy, a payment-authorization firewall for AI agents where the threat model is a prompt-injected agent moving money, so least-privilege, secrets hygiene and locked-down units are second nature. For your trial box: OpenClaw pinned, dedicated non-sudo user, local npm prefix, hardened systemd unit, everything loopback-bound except 22, UFW default-deny, SSH key-only with root and passwords off, fail2ban on sshd, secrets in 0600 EnvironmentFiles never in units or history, plus Netdata and CrowdSec for metrics and behavioral blocking (happy to defend that over plain fail2ban).

2. Closest thing I’ve built: https://www.npmjs.com/package/@fidacy/openclaw-plugin

3. Trial: fixed at USD 300. Ongoing: USD 65/hour.

4. Timezone: Lisbon (UTC+1). I run async and can usually jump on something urgent within the hour during my day, and happy to overlap your evening for handoffs.

If the throwaway box is ready, point me at it and I’ll turn it around fast.

30

Hi James,

This is the kind of practical agent/workflow work I like: make it run reliably on a real VPS, document it properly, and leave the client with something maintainable.

On the Telegram photo question: I would keep the agent away from guessing. The Telegram bot should capture the file_id, sender/user id, message id, timestamp and caption/context. n8n should then match it to the monday.com job using something deterministic: job number, QR/barcode, selected active job, or a short review queue when the match is not clear. I’d store the image outside Telegram in durable job-keyed storage, then write the storage URL, Telegram message id, sender and timestamp back to the monday.com record. I’d also make that step idempotent so one photo/message cannot create duplicate job updates.

One useful link: https://www.saharstudio.com/

I’m Marina from SAHAR Studio. My work is around AI agents, workflow automation and product builds using Codex/OpenClaw-style tooling, APIs, Python and Composio/tool-use. A lot of the work I do is internal systems rather than polished public case studies, but this OpenClaw/VPS/runbook task is very close to my current setup.

For the paid trial, I’d quote USD 580 fixed. That would cover Ubuntu 24.04 setup, a dedicated non-sudo user, pinned OpenClaw install, local runtime, systemd service, SSH key-only login, UFW, fail2ban, loopback-bound services except SSH, env files with 0600 permissions, CrowdSec + Netdata if you still want that stack, plus a short runbook and screen recording.

For ongoing work, I’d usually do USD 70/hour, or fixed-price per box/workflow once the scope is clear.

Timezone: Johannesburg, SAST / UTC+2. For urgent break/fix, I can usually respond within 2-4 hours during my working day and same day outside that. If you need stricter production coverage, I’d rather define that clearly before taking responsibility for it.

31

Hi James,

  1. For the Telegram photo → job record flow:
    When the staff sends a sign photo via Telegram, the bot captures the
    file_id, sender identity, timestamp, and caption. The safest approach
    is requiring a job number in the caption — but if that’s inconsistent,
    n8n can match by sender’s Telegram user against their active assigned
    job. Once matched, n8n downloads the file from Telegram immediately
    (file_ids don’t last forever), moves it to stable storage, then writes
    the file URL, message_id, sender, and timestamp back to the correct
    Monday.com job record. If the match is ambiguous, it goes to a review
    queue with a prompt back to the staff member — never a silent wrong
    attachment.

  2. Most relevant thing I’ve built:
    A WhatsApp-based field reporting system for a multi-location HSE
    operation (5 areas across Sumatra). Staff send unstructured reports
    via WhatsApp group → Fonnte webhook → n8n → Gemini AI parses the
    message and extracts structured fields → appends to Google Sheets,
    then sends an auto-confirmation reply back to the sender. Same
    core pattern as your setup: chat-based photo/data intake, AI
    parsing, structured record update, confirmation loop. Production
    deployed, self-hosted n8n on VPS.

  3. Trial quote: USD 200 fixed.
    Ongoing: USD 20/hour.

  4. UTC+7 (Palembang, Indonesia — overlaps well with Australian
    mornings). Urgent response: within 1–2 hours during my working
    day, same day outside that.

— Jack

32

Hi James — answering the four items directly.

  1. I’d make the job association explicit instead of asking the agent to guess from a caption. The bot can start from a job-specific button/deep link, or ask the sender to choose an active job, then fetch the photo with Telegram getFile and stream it into durable object storage under that job ID. I’d write an attachment row with the job ID, object key, Telegram message/update ID, sender, timestamp and hash, with a unique constraint on job ID + file_unique_id so retries are harmless. If the job is missing or ambiguous, the photo goes to a small review queue and the sender is prompted to pick the job before anything is linked.

  2. Closest public build: feat: add APort n8n passport router by M4dotsuki · Pull Request #74 · aporthq/aport-integrations · GitHub — an n8n community node with credential handling, two-output routing, an importable workflow and focused tests. It isn’t a VPS deployment, so I don’t want to pretend otherwise; it is the closest public automation sample I can point to.

  3. Fixed quote for the trial: USD 250. Ongoing: USD 35/hour. That includes the hardened host, a short runbook and a captioned screen recording; no camera or live call needed.

  4. Asia/Seoul (UTC+9). I can usually acknowledge urgent items within two hours between 09:00 and 23:00 KST, and by the next morning outside that window. I won’t pretend to offer 24/7 coverage.

For transparency, the implementation and documentation are AI-assisted. The actual host state — ports, service user, file modes, systemd restart behavior, firewall, fail2ban/CrowdSec and monitoring — will be checked on the VPS before handoff.

33

Hi James,

  1. I would have the Telegram path capture the file ID, sender, timestamp, and a stable job reference from the caption, reply context, or a required confirmation step. n8n would copy the image into durable job-keyed storage, validate that the job exists in Monday.com, and then write the image URL plus source message metadata back to that record. A missing or ambiguous job match would go to a human confirmation queue rather than being guessed. The write would be idempotent so a retry cannot attach the same photo twice.

  2. The closest public reference I can share is Loopwatch: Loopwatch reference build — Pragmatic Loop . It is a self-directed FastAPI/Docker reliability build with health checks, bounded retries, permanent failure states, run history, and operator handoff evidence; it is not client work or proof of OpenClaw production delivery. To be equally clear, I have not yet shipped OpenClaw in a client production environment, so I would prove that exact fit only through your paid throwaway-host trial rather than claim experience I cannot evidence.

  3. Fixed trial quote: USD 650 for the one fresh host, hardening, monitoring setup, verification, short runbook, screen recording, and one bounded correction pass. Ongoing work: USD 65/hour with a separately agreed weekly cap and support window.

  4. Timezone: Europe/Riga. I can usually respond within 2–4 hours in an agreed working window, and otherwise within the same business day; this does not include 24/7 or pager coverage.

If that honest proof boundary works for you, I would first confirm the exact OpenClaw version/source, the client’s recovery path, allowed monitoring exposure, and the acceptance checks before touching the fresh host.

Best,
Vladislav Bogdanov

34

@James_Nation — confirming that my application is now live after moderation. I remain interested in the bounded paid trial on the terms stated in post #33. Happy to answer any scope questions before access is shared.

35

  1. I would make the job association explicit: require a job ID, QR code, or bot job selection before accepting the finished-sign photo. The Telegram webhook gives n8n the file_id, message_id, sender, and caption; n8n should immediately resolve getFile and copy the bytes to S3, R2, or MinIO under a job-keyed path. It should then verify the job through monday.com, write the durable URL, content hash, and source message ID back idempotently, and send a confirmation. Missing or ambiguous job matches should go to a review or confirmation route rather than being guessed.

  2. tinyopsstudio dot com slash openclaw-vps-agent-host-setup

That is a TinyOps-owned implementation and handoff design, not a client case study. TinyOps has not yet shipped OpenClaw in a client production environment.

  1. Trial: $450 fixed for the stated fresh-host scope, including the working host, concise runbook, validation evidence, and narrated screen recording. Ongoing: $65/hour, scoped and approved before work.

  2. TinyOps operates on America/New_York (UTC-4). For urgent issues, response is generally within two hours during 08:00-20:00 ET; prearranged critical coverage can use a one-hour target. We can start within one business day of receiving fresh VPS access.

36

Hi James,

1. I’d have the Telegram bot fire an n8n webhook the second the photo lands, carrying the file, the caption, the sender and the timestamp. The link to the right job comes from whatever is most reliable on your floor: a job number in the caption, a QR or barcode on the sign that I read straight off the image, or a fallback where the bot simply asks “which job is this?” when nothing matches. Once I have a confident match in Monday.com I attach the image to that item, or push it to object storage and write the URL back onto the item once your archive gets large, along with who sent it and when. If the match is low confidence I route it to a small review queue instead of silently pinning it to the wrong job, because a mislinked sign photo is worse than one that waits ten minutes for a human glance.

2. Closest match I’ve built: an OpenClaw pipeline running on a self-hosted VPS that researches, validates and publishes content end to end, with a separate layer driving real browser sessions to post and reply on X and LinkedIn without tripping bot detection. Same shape as your stack, agents on a hardened box with n8n handling the deterministic glue and Telegram in the loop. Overview of my automation work: https://www.linkedin.com/in/lamichhanenishant/

3. Trial: fixed 250 USD for the hardened OpenClaw box exactly as you scoped it (pinned install, dedicated non-sudo user under systemd, SSH key-only, UFW, fail2ban, everything loopback-bound except 22, secrets in 0600 env files, plus the runbook and a screen recording). On monitoring I’d lean CrowdSec and Netdata for the reasons you named, and I’ll justify anything I swap. Ongoing: 45 USD/hr, or fixed milestones for larger builds.

4. I’m on Nepal time, UTC+5:45, about four and a half hours behind eastern Australia, so our working days overlap most of the day. For anything production-impacting I can usually be on it within 30 minutes during my day and within a couple of hours overnight.

Happy to start on the throwaway box whenever you want to hand one over.

Best,

Nishant

37

Hi, this one is right in my wheelhouse. I run OpenClaw agents on a self-hosted VPS myself, with n8n handling the deterministic parts, so the setup you are describing is what I already work with.

1. When the photo lands, the Telegram trigger in n8n grabs the file plus the message context. I would pull the job reference from that message, whether that is a job ID in the caption, a reply to the job’s earlier message, or the sign’s QR or barcode if it is in frame, then store the image in object storage (S3-compatible, with a backup on the VPS) and write a row linking that file URL to the right job record in monday.com. If the job reference is missing or ambiguous, I would have the agent ask the sender to confirm the job number rather than guess, so a photo never gets silently linked to the wrong job. I would also log the raw Telegram payload so nothing is lost if a parse fails.

2. Closest match: a self-hosted OpenClaw plus browser-automation pipeline I built for a client. It is a private system so I cannot share a public link, but I am happy to screen-record a walkthrough and send my LinkedIn on request.

3. Trial task: 200 USD fixed to turn the fresh Hetzner box into a hardened OpenClaw host as you described (pinned version under systemd, dedicated non-sudo user, local npm, SSH key-only, UFW, fail2ban, loopback-bound except 22, monitoring), handed back with a short runbook and a screen recording of the important parts. Ongoing work: 40 USD per hour.

4. Timezone: Nepal, UTC+5:45. I keep flexible hours and can usually jump on something urgent within a couple of hours, faster during my day.

Happy to start on the throwaway box whenever you are ready. Best way to reach me is nishant at skillsvital dot com

38

Hi my name is Abraham, i would love to learn something new, im a fast learner and i am avail 24/7.

39

Hi James,

  1. I would require a stable job reference before accepting the finished-sign photo: a job ID in the caption, a QR/barcode, or an explicit bot selection. The Telegram path would preserve file_id, message_id, sender and timestamp; n8n would fetch the bytes, hash them, store them under a job-keyed S3-compatible path, validate the monday.com item, then attach the durable URL and source metadata idempotently. Missing or ambiguous matches would go back to the sender for confirmation rather than being guessed. That also prevents a Telegram retry from attaching the same photo twice.

  2. One current public scope/payment reference: 24-Hour AI Automation Rescue Sprint by Jimmy Cater . To be precise, this is an active prepaid automation service page, not a claim of prior OpenClaw client delivery. I would prove this exact fit on your throwaway-host trial and will not represent a private or unrelated build as evidence.

  3. Fixed trial quote: USD 1,250 for the stated fresh Ubuntu 24.04 host, pinned OpenClaw install, dedicated non-sudo service account, systemd, SSH/UFW/fail2ban hardening, loopback exposure checks, CrowdSec/Netdata or a documented alternative, secrets permissions, recovery verification, concise runbook, narrated screen recording, and one bounded correction pass. The trial starts only after 100% is funded through Contra. Ongoing option: USD 1,500/month prepaid for up to 12 hours of agreed maintenance, additional boxes/workflows, and break/fix work; anything beyond that is separately approved before work.

  4. Timezone: Asia/Seoul, UTC+9. I can normally respond within 2–4 hours during an agreed coverage window and the same business day otherwise; I would define any production-critical response commitment in writing before taking responsibility.

I can start once the funded milestone, exact OpenClaw source/version, fresh-host access boundary, and acceptance checks are agreed.