Lead AI Agent Engineer
We're building intelligent products powered by LLMs and autonomous agents — and we're looking for someone to lead that work.
This isn't a "we want to explore AI someday" role. We already run agentic systems in production: multi-agent orchestration, automated workflows handling real business operations, and tool-using agents connected to live APIs. We need a builder who can take ownership of this — set the technical direction, raise the standard, and ship agents that actually work.
If you've built agents that do real work — not demos, not Twitter threads, actual deployed systems — keep reading.
Who thrives here
You think like a builder, not just a coder. You're genuinely curious about where this technology is heading. You can work independently but communicate clearly. You'd rather ship something real and improve it than over-plan in theory. And you care — when something isn't ready, you say so.
How to apply
We care about substance over buzzwords. Use the form below — and in your cover letter, tell us about one thing you've actually built with AI agents. A repo, a demo, or a short description of a system you shipped and what it does.
Shortlisted candidates will be invited to a short practical assignment — real problems, no AI-generated answers, just your thinking.
Let's build intelligent systems people actually love using. ✨
What you'll do
- Lead the architecture and development of our agentic AI products.
- Design and build multi-agent systems — orchestration, tool use, memory, evaluation.
- Work hands-on across the stack. This is a building role, not just a planning one.
- Integrate LLMs with real APIs and automation pipelines.
- Make smart calls on model routing, cost, latency, and reliability.
- Set engineering standards and review work — own quality before anything ships.
- Mentor a young, motivated team and help level them up.
Requirements
- Real, hands-on experience building and deploying AI agents — this is a hard requirement.
- Experience with agent frameworks, orchestration, and tool / function calling.
- Strong command of LLM APIs, prompt engineering, and the judgment to know when NOT to use an LLM.
- A solid full-stack foundation — modern JavaScript frameworks, and ideally Python.
- Comfort with APIs, automation, deployment, and basic infra (VPS, CI/CD).
- The architectural sense to choose the right approach for the problem.
- Ownership — you catch the issues before users do.
Nice to have
- Experience with MCP (Model Context Protocol).
- Built agent evaluation or observability systems.
- Worked with self-hosted or routed model setups (OpenRouter and similar).
- Background leading or mentoring other developers.
Benefits
- A full-time role with real ownership of our AI direction.
- Hybrid setup — work from our Rajshahi office or from home, your choice.
- Flexible hours.
- A young, international team that moves fast.
- Freedom to experiment with emerging tools and architectures.
- Direct influence on product decisions.
- Performance-based growth — your impact is visible here.