Support Engineer/Developer - Deep Technical Support

🛠️ Support Engineer/Developer - Deep Technical Support

Debug Production. Ship Fixes. Own Customer Success.

Ender Turing's AI speech analytics platform processes millions of conversations across 20+ integrations. When enterprise clients hit edge cases at 6 AM, you're the one who dives into logs, traces the issue through

microservices, and ships the fix before their morning standup.

Your Mission: Be the Technical SWAT Team

- Production Debugging: Trace issues through FastAPI services, Celery queues, OpenSearch clusters

- Integration Support: Debug webhook failures, API timeouts, data pipeline issues across Zendesk, Genesys, Five9, etc integrations

- Customer Code Reviews: Analyze client implementations, spot bottlenecks, optimize their API usage

- Hotfix Development: Write Python/TypeScript patches that go straight to production

- Infrastructure Triage: SSH into servers, analyze Docker logs, query PostgreSQL, hunt memory leaks

Daily Reality Check

09:00 - Customer reports transcription delay -> Check Celery queue backlog

10:30 - Write Python script to reprocess 10K stuck sessions

12:00 - Debug WebSocket connection drops in Vue dashboard

14:00 - Trace OpenSearch query timeout, optimize index mapping

16:00 - Ship hotfix for Genesys integration parsing edge case

18:00 - Document root cause, update runbooks, improve monitoring

Your Toolkit

Languages: Python, SQL, Bash (sometimes, TypeScript/JavaScript)

Backend: FastAPI, Celery, PostgreSQL, SQLAlchemy

Infrastructure: Docker, Linux

Monitoring: Sentry, custom logging pipelines

Integrations: REST APIs, Webhooks, OAuth flows, CRM systems

Non-Negotiable Skills

✅ 3+ years in technical support and/or DevOps with coding skills

✅ Debug Mastery: Can trace a bug through 5 microservices using only logs

✅ SQL Ninja: Complex queries, query optimization, database debugging

✅ API Debugging: Postman, curl, reading logs and traces in your sleep

✅ Docker and Linux Comfort: SSH, grep, tail -f, docker service ls is your natural habitat

✅ Customer Communication: Explain technical issues without condescension

You're Perfect If You

- Get excited seeing "500 Internal Server Error" (finally, a real problem!)

- Have a personal collection of debugging scripts you've written

- Can explain distributed systems failures using restaurant analogies

- Think "Works on my machine" is a personal failure

- Actually read stack traces instead of copying them to ChatGPT

Support Philosophy We Live By

🔍 Root Cause > Quick Fix (but ship the quick fix first)

📊 Data Drives Decisions - reproduce, measure, fix, verify

🚀 Every Ticket = Product Improvement - bugs become features

💪 Own the Problem - no "that's not my department"

🧠 Teach While Fixing - empower customers to self-serve

What Makes This Different

Not Your Typical Support Role:

- You'll commit code to production repos PR’s

- You'll architect solutions, not just follow runbooks

- You'll pair with senior engineers on system design

- You'll influence the product roadmap with field insights

Growth Path:

- Support Engineer → Platform Engineer → SRE Lead

- Or: Support Engineer → Solutions Architect → Customer Success Engineering Lead

Real Scenarios You'll Handle

1. The Integration Mystery: "Calls from Genesys contact center system stopped syncing at midnight" - trace through logs, identify API rate limit, new fields in JSON answer, implement new structure support

2. The Performance Hunt: "Dashboard takes 30s to load" - profile PostgreSQL queries, add caching layer, optimize SELECT query

3. The Data Puzzle: "Transcripts missing for 500 calls" - track through Celery tasks, find S3 permission issue, fix the lambda function, reprocess if needed

4. The Scale Challenge: "System slows at 10K concurrent sessions" - identify bottleneck, implement queue prioritization, deploy fix

Interview Process

1. Culture Fit (20 min): How you handle pressure, angry customers, and impossible deadlines

2. Technical Screen (20 min): Debug a real production issue

3. Deep Dive (30-45 min): Architecture discussion, live debugging session, SQL challenges

4. Take-home (1 hour): Given logs and error reports, find the root cause and propose a fix

What We Need From You

📧 Send us:

- Your most clever debugging story (the weirder, the better)

- GitHub/GitLab profile or code samples

- Proof you can write (documentation, blog posts, detailed bug reports)

- Your home lab setup (optional, but we're curious)

Compensation & Perks

💰 Competitive salary

🎯 Direct impact on product and thousands of users

🏠 Full remote (but you need to overlap 4 hours with CET timezone)

Red Flags (Don't Apply If)

❌ You think customers are "annoying"

❌ You prefer perfect documentation over diving into code

❌ "That's a development issue" is in your vocabulary

❌ You need detailed instructions for every task

❌ You think AI will replace debugging skills

Green Flags (Definitely Apply If)

✅ You've built home labs to reproduce customer issues

✅ Your browser has 50+ tabs of documentation open

✅ You've contributed to open source projects' issue trackers

✅ You can explain why "restart fixed it" isn't a solution

✅ You get genuinely excited about elegant solutions to ugly problems

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🔥 Join us while the codebase is still small enough to understand fully.

P.S. - If you've ever fixed a production issue during a holiday dinner and felt proud rather than annoyed, you're the kind of engineer we're looking for.