AI Engineer

At Endgame

• Ability to make an impact: Be part of the company which values results
• Grow fast. Work as a part of a top engineering team
• Build, build, build: start your own pet project, we will mentor and advise
• BYOTS: bring your own tech stack. Ability to explore and influence the decisions
• Perks: laptop, fancy tools, vacations, remote work, all usual stuff
   

Why

• Because 80% of enterprise software is garbage
• Because long discussions without valuable action can be tiresome
• Because small, diverse expert teams outperform armies
• Because we know how to build faster than yesterday
• Because great engineers deserve better

We're building the alternative.
 

What We Do

• Deliver working products, not slides
• Unbreak enterprise software
• Ship in weeks, not quarters
• Smaller teams, senior only
   

The Job

• Build AI systems that actually work in production
• Ship LLM-powered features that solve real problems
• Own the entire pipeline — data → retrieval → prompts → tools → evals → production.
• Ship with guardrails: safety filters, PII handling, audit logs
• Turn messy problems into working AI features (LLMs, RAG, agents)
• Choose models and stack pragmatically (build, buy, or fine‑tune)
• Optimize cost, latency, and reliability (caching, batching, streaming)
• Measure everything: offline eval harness + online A/Bs
• Talk to clients about what's possible, not what's hype
• Code. No hand‑offs
• No bureaucracy
   

You

• Shipped AI/ML systems in production (not just demos)
• Built systems that scale beyond ChatGPT copy-paste
• Built RAG systems that actually retrieve the right context
• Experience with real-world LLM ops — monitoring, evaluation, cost optimization
• Fixed more weird failures than you caused (hallucinations, drift, token limits)
• Senior or higher; strong product taste and bias to action
• Communicate clearly — explain transformers to CEOs and tokens to engineers
• Obsessed with making AI useful, not just clever
• Treat prompts/data like code — versioned, tested, reproducible
• Own what you ship — from system prompt to API response
   

Your Stack and Experience

• Deployed and maintained LLM applications in production environments
• Proficiency with: Python, LLM SDKs (OpenAI/Anthropic/Azure/Bedrock/Cohere), orchestration & agents (LangChain/LangGraph or equivalent)
• Experience with vector databases (Pinecone, Qdrant, pgvector)
• Evals & observability: Ragas/TruLens, Langfuse/Helicone, OpenTelemetry
• Big plus: Workflow automation and low-code AI tools (n8n, Langflow, Flowise)
• Prompt engineering, function calling, agent frameworks — the whole toolkit
• Big plus: ML experience and TensorFlow knowledge for when LLMs aren't the answer
   

We Don't Want

• Process evangelists
• Architecture astronauts
• Meeting enthusiasts
• Supervision required
   

The Deal

• Competitive Salary
• Good bonus
• Decent learning budget
• AI tools
• Remote with occasional travel

Anything missing, tell us.
 

FAQ

Q: Remote?
A: Yes. Anywhere CET +/- 2 hours.

Q: Work-life balance?
A: Work hard. Rest well. No weekends unless prod is on fire.

Q: Growth path?
A: Build products → Run practices → Build the company

Q: Why "Endgame"?
A: Because we're building what comes next.
 

That's it.
You either get it or you don't.
If you get it, we should talk.
 

Equal opportunity employer.
We judge only on ability to ship products.