- Insiderone
- Turkey,
- Full-Time
- 10 days ago
Software Engineer - (AI Native).
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Software Engineer - (AI Native): our view in 3 lines...
- The Role:This role is for a software engineer who already uses coding agents on real production work and wants to build software with them.
- The Person:The person will scope, implement, test, review, debug, and ship production features with coding agents, while building prompts, sub-agents, MCP integrations, guardrails, tests, and AI-assisted review workflows.
- Requirements:The ideal candidate has daily use of coding agents, at least one end to end project with these tools, agentic experience, solid engineering fundamentals, Go and PHP/Laravel preferred, and experience with Python or TypeScript.
About the role
About the role
Most engineering teams have added AI to their workflow. A few have rebuilt their workflow around it. We are moving to the second group, and we are hiring engineers to build it with us.
This is not a role where you build LLM products. This is a role where you build our product with agents.
You will work inside a real, high-traffic production codebase: the platform that 2,000+ brands use to engage customers across channels, processing 2.2 billion requests and delivering nearly 2 billion notifications every day. You will plan, implement, test, review, debug and ship features with coding agents doing most of the writing, while you set the intent and own the outcome.
You are not expected to arrive with a company-wide standard in your head. You are expected to already work this way every day, and to leave the team with better prompts, skills, agents and guardrails than it had before you.
If your first reaction to a repetitive workflow is "this should be an agent," we should probably talk.
Why this role exists
We looked at how our engineers work today. Some of them use AI to finish a line of code faster. That is autocomplete, and it is not what we mean.
We mean the full loop: you scope a change, an agent reads the codebase and writes a plan, you correct the plan, the agent implements across many files, runs the tests, fixes what it broke, and opens a pull request. You review the output like a senior engineer reviews a junior — because that is exactly what it is.
Some people already work like this every day. We want more of them on the team, and we want them building the tooling that makes it easy for everyone else.
