# 🎯 Killer Application Guide — Full-Stack Engineer @ Calvana LTD

---

## 📋 JOB REVIEW SUMMARY

### Company: Calvana LTD
- **B2B SaaS startup** solving client acquisition for B2B companies
- Starting by dominating the "internet marketing" agency & coaching market
- Claims: cash ✅, audience ✅, distribution ✅, product-market fit ✅
- Looking for **first engineering hires** — massive ownership opportunity
- Has a Loom video: https://www.loom.com/share/1e6f7f6255d74e7785a7a8e48c2d5788
- $2,000 referral bonus signals they're actively hunting

### Role: Full-Stack Engineer (Early Hire)
- **Location:** Remote (ideally London timezone)
- **Type:** Full-time
- **Stack:** Next.js (frontend) + Django/PostgreSQL (backend) + Pulumi/AWS (infra)
- **Nature:** End-to-end ownership, microservices, AI-powered features, 3rd-party API integrations

### 🔑 What They REALLY Want (Reading Between the Lines)
1. **A builder, not an employee** — someone who acts like a co-founder
2. **Self-directed** — no PM, no Figma specs, no hand-holding
3. **Speed over perfection** — ship fast, iterate, "high velocity"
4. **AI-native** — not just curious, but has actually BUILT with AI APIs
5. **Full ownership** — from idea → architecture → code → deploy → monitor
6. **Communication** — small team, you explain your own decisions

### ⚠️ Red/Yellow Flags to Be Aware Of
- "Multi-billion dollar vision" is ambitious language — be prepared for startup chaos
- "No AI screening" = the founder (Charlie) reads every app personally → **personalize everything**
- Early hire = wear many hats, likely no work-life balance initially

---

## 📝 APPLICATION FORM — FIELD-BY-FIELD STRATEGY

The Google Form has **14 fields**. Here's how to make each one count:

---

### 1. Full Name *(required)*
> Just your name. No tricks here.

### 2. Email Address *(required)*
> Use a professional email. If you have a custom domain, use it — it signals you're technical.

### 3. LinkedIn / Personal Site / Portfolio *(required)*
> **Priority order:** Personal site > LinkedIn > Portfolio
> If you have a personal site with projects, that's gold. It shows you ship.
> Make sure your LinkedIn headline matches what they want: "Full-Stack Engineer | Next.js + Django | Building AI-powered products"

### 4. GitHub or Equivalent *(required)*
> **Make sure your pinned repos showcase:**
> - A full-stack project (React/Next.js + Python backend)
> - Something with AI/ML APIs
> - Clean READMEs with screenshots, architecture diagrams
> - Recent commit activity (shows you're active)

### 5. Location *(required)*
> Be honest. If you're not in London, emphasize timezone overlap willingness.
> Example: "Manila, Philippines (happy to work London hours / significant overlap)"

### 6. Employment Status *(required, radio)*
> Options: Employed full-time | Employed part-time | Between roles | Freelancing | Running my own thing
> **"Running my own thing" or "Freelancing"** are the strongest signals for this role — it shows self-direction.
> "Employed full-time" is fine too — shows you're in demand.

---

### 7. 🔥 CRITICAL: "Describe something you built end-to-end" *(required)*

**This is the MAKE-OR-BREAK question.** They explicitly want: problem → decisions → deployment.

**Structure your answer like this (aim for 200-350 words):**

```
PROBLEM: [1-2 sentences — what pain point existed]

WHAT I BUILT: [What the product/feature was, who it served]

KEY DECISIONS:
- Chose [X] over [Y] because [reason] → shows architectural thinking
- Used [specific tech] for [specific reason] → shows you don't just follow tutorials
- Handled [edge case/challenge] by [solution] → shows production mindset

RESULT: [Quantifiable if possible — users, performance, revenue, time saved]

SHIPPED TO: [Where it's live — URL, app store, internal tool]
```

**EXAMPLE (adapt to your experience):**

> I noticed freelancers in my network were losing 5-10 hours/week manually creating client proposals. I built ProposalPilot — an AI-powered proposal generator.
>
> Frontend: Next.js with TailwindCSS, deployed on Vercel. Backend: Django REST API on AWS ECS with PostgreSQL. The AI pipeline used OpenAI's API for content generation and a custom prompt chaining system I built to maintain brand voice consistency across sections.
>
> Key decisions: I chose Django over Express because I needed robust ORM support for complex relational data (clients, templates, proposal versions). I containerized each service with Docker and used GitHub Actions for CI/CD. For the AI layer, I implemented streaming responses so users see content generating in real-time rather than waiting 15-20 seconds for a full response.
>
> The hardest part was handling rate limits and failures from OpenAI gracefully — I built a retry queue with exponential backoff and a fallback template system so proposals never fail completely.
>
> Result: 40+ active users, avg. proposal creation time dropped from 3 hours to 20 minutes. The project is live at [URL].

---

### 8. Link to Something You've Built *(optional but DO IT)*
> This is your proof. Link to:
> - A live product URL (best)
> - A GitHub repo with a stellar README + demo GIF
> - A Loom walkthrough of your project
> - A technical blog post about the build

### 9. 🔥 AI/ML API Experience *(optional but CRITICAL for this role)*

**They specifically mention: OpenAI, ElevenLabs, Replicate, Whisper, Stable Diffusion**

**Structure:**
```
WHAT I BUILT: [Specific project using AI APIs]
APIS USED: [List them — the more the better]
WHAT I LEARNED: [Focus on production challenges, not just "I called the API"]
```

**EXAMPLE:**

> I built an AI voice-over tool for content creators using ElevenLabs for TTS, OpenAI for script optimization, and Whisper for transcription/captioning. The pipeline: user uploads a script → GPT-4 optimizes it for spoken delivery → ElevenLabs generates audio with voice cloning → Whisper generates timestamped subtitles.
>
> Key learnings: ElevenLabs' streaming API is great for previews but you need the non-streaming endpoint for production-quality audio. I learned to manage API costs by implementing a caching layer — identical scripts don't regenerate audio. Also built a webhook system since audio generation is async and can take 10-30 seconds for long content.
>
> The biggest insight was that prompt engineering for TTS scripts is fundamentally different from chat — you need to engineer for prosody, pacing, and emphasis, not just content accuracy.

---

### 10. Tech Skills Grid *(required)*

Rate honestly — they'll verify in interviews. Here's the scale:
| Tech | never used | used once | decent | strong | production-level |
|------|-----------|-----------|--------|--------|-----------------|
| React / Next.js | | | | ← aim here | ← or here |
| Python / Django | | | | ← aim here | ← or here |
| PostgreSQL | | | | ← aim here | ← or here |
| AWS | | | ← minimum | ← ideal | |
| REST API design | | | | | ← aim here |
| OAuth | | | ← minimum | ← ideal | |
| CI/CD | | | ← minimum | ← ideal | |
| Docker | | | ← minimum | ← ideal | |

**Don't lie.** "Decent experience" with honesty beats "production-level" that crumbles in an interview.

---

### 11. 🔥 "Why does this role interest you?" *(required)*

**DO NOT write generic "I love startups" garbage.** They read every application personally.

**Formula: Mirror their language + show you understand the stage + add a personal hook**

**EXAMPLE:**

> Three things stood out:
>
> First, the ownership. I've worked in teams where I owned a component, not a problem. You're describing the opposite — pick up a problem space, scope it, build it, ship it. That's exactly how I work best. My best projects happened when nobody told me what to build.
>
> Second, the timing. Being an early engineering hire at a company with existing revenue and PMF is the sweet spot. You've de-risked the "will anyone pay for this?" question, and now it's about building fast enough to capture the market. That's where I thrive.
>
> Third, the stack and the AI angle. I've been building with Next.js and Django professionally, and I've been deep in the AI API ecosystem for the past year. The idea of owning AI-powered features end-to-end at a company that's actually shipping (not just experimenting) is exactly where I want to be.
>
> I watched the Loom — Charlie's energy and clarity about the vision is compelling. I want to be part of building this.

**(Note: mentioning the Loom video by name shows you actually watched it — huge signal)**

---

### 12. Salary Expectation *(required)*
> Research tips:
> - Remote full-stack roles in London-adjacent timezone: £50k-£80k+ for early hires
> - If you're outside UK, adjust for cost-of-living but don't lowball yourself
> - Frame it: "$XX,000 USD / year — open to discussion based on equity/benefits package"
> - Showing flexibility on comp structure (salary + equity) signals founder-mindset

### 13. How Soon Could You Start? *(required)*
> **"Immediately" or "< 2 weeks"** are strongest signals for an early-stage startup that needs to move fast.
> If you need to give notice, "< 1 month" is still fine.

### 14. Loom Video *(optional — but THIS is your secret weapon)*

**This is how you separate yourself from 95% of applicants.**

**Record a 2-minute Loom with this structure:**
- **0:00-0:15** — "Hi Charlie, I'm [name], [one-line positioning]"
- **0:15-0:45** — Quick walkthrough of something you built (screen share a project)
- **0:45-1:30** — Why THIS role specifically (mirror their language: ownership, velocity, AI)
- **1:30-2:00** — "Here's what I'd build first if I joined" (show you've thought about their product)

**Tips:**
- Use their founder's name (Charlie — from the Loom video)
- Show energy and enthusiasm — match their "going to the moon" vibe
- Share your screen showing a real project, not just a talking head
- Keep it under 2 minutes — respect their time

---

## 🏆 APPLICATION CHECKLIST

Before you submit, verify:

- [ ] GitHub pinned repos are updated with best projects + clean READMEs
- [ ] LinkedIn headline/summary reflects full-stack + AI capabilities
- [ ] "Built end-to-end" answer follows Problem → Decisions → Result structure
- [ ] AI/ML answer shows PRODUCTION challenges, not just tutorial-level usage
- [ ] "Why this role" mentions specifics from THEIR posting (Loom, microservices, PMF)
- [ ] Salary research is done — give a confident range
- [ ] Loom video recorded (2 min, high energy, shows a real project)
- [ ] All required fields filled (13 required, 1 optional)
- [ ] Re-read everything — no typos, no generic language

---

## 💡 POWER MOVES (Stand Out Tactics)

1. **Build a mini demo** — Before applying, spend 2-4 hours building a tiny microservice that solves a problem relevant to their space (e.g., an AI-powered lead qualifier). Link it in your "built something" answer. Nothing says "I ship" like shipping something FOR them.

2. **Reference the Loom** — The founder recorded a 7-minute Loom. Most applicants won't watch it. Reference specific things from it to prove you did.

3. **Show, don't tell** — Every claim should have a link, a repo, or a demo. "I've built with AI APIs" < "Here's the repo where I integrated OpenAI + ElevenLabs: [link]"

4. **Think like a founder** — In your "why this role" answer, mention what you'd want to build first. Shows you're already thinking about their product, not just your career.

5. **Follow up** — If you can find Charlie on LinkedIn/Twitter, send a short "Just applied — excited about [specific thing]" message 24h after applying.
