Jobs at Djinni

About us

GigRadar is the market leader in our vertical: AI-powered lead generation on Upwork for agencies and freelancers. We remove the need for in-house bidding teams and multiply agencies' marketing efficiency.
 

A quick picture of who you'd be joining:

• Infrastructure trusted by 3,000+ Upwork agencies worldwide.
• 4.7/5 "Excellent" on Trustpilot, with 91% five-star reviews.
• 30K+ LinkedIn audience and a strong founder brand.
• Backed by a leading SalesTech/MarTech player (on our board)
• A product line of AI agents: Sardor AI (auto-bidder — finds relevant jobs, writes personalized cover letters, and submits within 15 minutes), Laziza AI (AI SDR — runs conversations, handles objections, books meetings), Upwork CRM, Upwork Analytics, and GigRadar Inbound.

We're not a day-one startup, and we're not a slow enterprise. We have a proven business model, a mature product, a fast-growing AI lineup, and clear leadership in our niche - confident operators growing fast.

And most importantly for this role: strong channels are already running.

• SEO — a dialed-in channel built entirely on AI agents.
• Email + LinkedIn outreach — its own team.
• Partner / referral network — its own team.

You're not here to patch holes but you're here to build a new amplifier vertical on top of a working machine. You won't have to prove the business works; it's been alive for years. You'll get to build your own growth engine and scale it. On top of that, we have a large library of ready material (case studies with numbers, Upwork Reports, community content, reviews) you can turn into powerful marketing.

The mission

Build and launch a new inbound-demand vertical that consistently generates 200–300 booked demos per month through organic content, an authoritative newsletter, and automated funnels from free products and automate it with AI, not manual labor or a bloated team.

You are a one-person orchestra.
Strategy, hypotheses, copy, landing pages, sequences, content, analytics — you run it yourself, using AI as your "extra hands" (design, copy, front-end, and research through AI tools, not contractors).

What you'll do

Lifecycle / CRM marketing (core)

• Build and monetize segmented work across the base: newsletter, unsubscribers and cooled-off leads, leads from the sales pipeline, leads from cold outreach. Different segments → different scoring → different sequences.
• Find the signals yourself and turn them into triggered sequences. Example signals: booked a demo but didn't show; read N newsletter issues; used a free product X times; sat in the pipeline for N days. These are examples — your job is to spot such signals and build flows around them.
• Reactivate the "sleeping" base (several thousand leads no longer worth active outreach but recoverable through sequences).

Newsletter as an asset

• Build a genuinely strong, authoritative newsletter — #1 in our space on building and scaling a business / lead gen on Upwork for service companies and freelancers. Not a "mailing list," but a media asset that grows the base and warms it toward demos.

Growth / organic

• Organic growth on LinkedIn and X (Twitter), plus experiments (Reddit, niche content, etc.): viral/value posts that feed funnels.
• Scale a network of established employee accounts (founder-led + team advocates) — not faceless farms, but real personal brands at varying stages that need to be systematized and amplified.
• Funnels from free products: lead magnet → email capture → nurture → auto-purchase of a paid product or a demo.

AI as the way you build it all "by hand"

• Build repeatable marketing systems on AI tools (Cowork, Codex, and similar): a content engine (agents pull data → assemble a content plan → turn it into posts), sequence generation, landing pages, calculators, banners — without pulling in developers or design studios.
• Mine our large internal content library into posts, funnels, and sequences — rather than inventing from scratch.

CRO / web / reputation

• Raise conversion on the site and landing pages (demo page, free-product pages).
• Work on brand reputation: systematic review responses (Trustpilot / G2, etc.), messaging, demo experience.

What we're looking for

We are looking for a marketer who applies AI brilliantly to marketing problems, not a developer placed on marketing.

• 3–5+ years in marketing, specifically in B2B SaaS for the US market.
• A strong foundation in conversion marketing: you crank conversion through meaning — audience pains and desires, purchase triggers, offer structure. That's your base, not just "having seen a lot."
• Proven cases with numbers: you personally wrote converting copy in newsletters/sequences and personally moved landing-page conversion — and can show "before → after."
• Proven volume: you've generated a comparable number of SQLs/demos (in the hundreds per month), not just "ran campaigns."
• Hands-on AI fluency: you already build marketing systems with AI (Cowork / Codex / etc.) and can validate what AI produces, not just publish it blindly.
• Fluent English.
• Ideal background: B2B SaaS in a close space including SalesTech, MarTech, GTM-tech that sold to agencies and service companies. Then you already know our buyer and need no ramp-up on the ICP. Candidates from an agency background aren't a fit; we need a product/SaaS background
• A hard requirement — everything hands-on. The "I assigned tasks to a team/contractors and they did it" profile isn't a fit. We need someone who did it themselves and owned the result.

Our stack

• HubSpot — the core: email, triggers, client documentation.
• AI-first analytics: our agents traverse HubSpot data and return analytics.
• Intercom — behavioral triggers and analytics for active clients.
• Pre-purchase leads — all in HubSpot.

Success metrics (KPIs)

• North star: booked demos per month — ramp to 200–300/month within 3–6 months.
• Newsletter: base growth + end-to-end conversion of the warmed segment to demos (target ~2–3%).
• Demo-page CRO: from a baseline ~2–4% to 6–8%+.
• Free → paid: toward the PLG median of ~9%+.
• Reactivation of the sleeping base: % of leads brought back.

Compensation

• Base: $2,500–3,500/month (depending on level).
• Performance bonus: $1,500–2,500/month at 100% of plan, tied to demos, SQLs, and pipeline contribution; quarterly accelerator for overperformance.
• OTE at 100% of plan: ~$4,000–6,000/month.
• Remote working
• Carrer path to CMO.

What to bring to the call with our team

• Cases with numbers — where you drove growth and which metrics you actually moved (not "the team did it"), including the volume of SQLs/demos generated.
• A live screen-share — show your AI layer (Cowork / Codex / etc.): what you build by hand as a marketer.
• Conversion-marketer thinking — how you crank conversion through audience pains/desires/triggers.

Remote · Full-Time · English async · Time Zones: CET +/- 2 hours · Reports to Founder

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ABOUT THE WORK

Riffbird is one of the largest social recruiting agencies in DACH, with 600 clients across Austria, Germany, and Switzerland. We run paid social campaigns, pre-qualify applicants on the phone, and operate the full hiring funnel for our clients.

The service works. The infrastructure does not. Today it runs on a patchwork of external SaaS tools held together by manual operator work. We're now bringing the operational layer in-house, piece by piece, and we're building it so LLM agents can do most of the work that humans currently do by clicking around.

You're coming in to build that layer. It's not a greenfield reinvention of recruiting software. It's the platform that turns an already-working service into something agents can run.

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WHAT YOU'LL BUILD

One platform, built around a single asset and a set of agents that operate on it.

THE DATA LAYER (the most important thing we own)

A unified candidate and client database. Every campaign, every screening call, every interview outcome feeds it. A candidate who doesn't fit Client A stays discoverable for Client B with proper consent. Full-text plus semantic search. This is the part of the business that's hardest to replicate from outside, and everything else on the platform exists to feed it, query it, or act on it.

THE AGENT WORKFORCE

The operational work we do today, moved one capability at a time onto agents that can run with human supervision:

• Ad creative generation (already live with Claude Code, gets expanded and integrated)

• Recruiting landing page generation, per client and per role

• Candidate research, active sourcing, and headhunting (LinkedIn, niche platforms, our own pool)

• Outbound qualification calls (telephony integration, region-by-region pitch and screening logic, full transcript and outcome tracking)

• Outreach and follow-up drafting

• Pipeline operations: moving candidates through stages, flagging stalled ones

• Reporting and anomaly detection across ad spend, funnel, and conversion

Our operators stay in charge of the work, the agents scale what they do. A capability moves from human-driven to agent-driven only when the evals back it up.

THE CLIENT WORKSPACE

Where our 600+ clients see their pipelines, get their reports, and talk to us. Multi-tenant, fast, clean. Today this is split across a stack of external tools and Slack, getting it in-house is step one.

THE AGENT PLATFORM

Typed, scoped tools, audit trails, eval pipelines, the infrastructure that lets us ship new agent capabilities without breaking client work. GDPR-clean throughout (German clients, German applicants, non-negotiable).

 

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WHAT YOU BRING

We don't care which language or framework you pick. We care that you've done the hard parts somewhere before:

• 5+ years shipping production systems where state, queues, webhooks, and idempotency actually mattered, not just CRUD over a single table

• Built and operated multi-tenant SaaS with a real permission model, not just WHERE tenant_id = ? stitched into every query

• Shipped LLM features in production where it had to work: RAG that retrieved the right thing, tool-calling that didn't hallucinate the schema, evals that caught regressions before users did

• Designed APIs and data models that agents can use without supervision, or at least understand what changes when the consumer is an LLM instead of a frontend

• Operate well in EU/GDPR territory, or have the discipline to learn it without us getting fined (in cooperation with our GDPR-expert)

• Async-remote operator: you write things down, you disagree in writing, you don't need standups

• Comfortable working directly with a founder who builds product himself with AI tools but isn't going to sparring-partner you on systems design. You own the engineering decisions, no PM in the middle. 

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WHO YOU ARE

You're already living in this stuff. You read what comes out of Anthropic and OpenAI in real time, you've shipped with the APIs, you have opinions about which eval frameworks actually work and which are theater. This is the role you've been waiting for, not the role you applied to because the comp was good.

You move fast, but you've been burned enough times to know when fast is reckless. You can hold that trade-off.

You want your name on something real, not be engineer number 47 on someone else's feature team.

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NICE-TO-HAVE

• Recruiting, HR-tech, or staffing-software experience

• Hired and led small engineering teams before

• Voice, telephony, or RTC experience

• Strong opinions about agent UX (what a tool should and shouldn't expose to an LLM)

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WHAT YOU GET

• Greenfield, full ownership. You pick the architecture, you pick the tools. No legacy code, no committee, no permission slip.

• A founder who ships. Bernd (founder) uses Claude Code daily and builds production tooling himself. You get a counterpart who understands what you're doing, not someone managing you from outside.

• Above-market pay. We won't quote a band on the public posting, but we definitely pay properly for this role.

• The opportunity to take full responsibility of the system architecture short-term and build a team to support you long-term.

• Tooling and hardware budget that respects your craft. Premium AI subscriptions, top-spec machine, conference and training budget, trips to the Bay Area when there's a reason.

• Optional two retreats a year. Austria and Dubai. Proper time together with the founder and core team, not Zoom.

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HIRING PROCESS

1. 30-min intro call with Bernd (founder)

2. 60-min architecture conversation, no leetcode, never

3. Paid pair-programming or take-home on a real Riffbird problem (4 to 8h, paid at market rate)

4. References, decision, offer within 7 days

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POSITION OBJECTIVE:

• System Developer – Custom AI & Multi-Agent Systems (Python / Gemini): is responsible for development to design, implement, and maintain a custom, production-grade AI system built in Python and powered by Google Gemini models.
• This role focuses on developing a multi-agent architecture that collaborates to solve domain-specific problems using a tightly controlled set of internal and external APIs.
• The developer will work closely with backend engineers and domain experts to ensure that AI outputs are accurate, explainable, and aligned with real-world system behavior.

RESPONSIBILITIES:

• Ensuring that AI agents interact with this platform in a reliable, deterministic, and secure manner, using well-defined API contracts and business rules. 
• Designing agent roles and coordination strategies, implementing prompt and tool-use logic, and managing context boundaries so agents operate efficiently within defined data and API limits.

• Building supporting infrastructure such as agent orchestration logic, error handling and fallback mechanisms, observability and logging, and test harnesses for validating agent behavior against known scenarios.

   

REQUIREMENTS:

• Strong proficiency in Python, including production-quality code, testing, and debugging
• Hands-on experience integrating large language models, preferably Google Gemini
• Experience designing or working with multi-agent or tool-augmented AI systems
• Familiarity with RESTful APIs and secure service-to-service communication

• Solid understanding of system design, state management, and asynchronous workflows

   

PREFERRED QUALIFICATIONS:

• Experience working with geospatial, telemetry, or fleet-tracking data
• Background in backend systems, distributed services, or data pipelines
• Experience with AI evaluation, prompt iteration, and model behavior analysisderstanding of the full mobile development lifecycle.

WHAT WE CAN OFFER YOU:

• Paid vacation and sick time 
• Public holidays 
• Technical equipment
• Happy hours on Fridays
• Company sponsored events as well as a casual work environment

SALARY COMMENSURATE WITH EXPERIENCE