Full Stack Engineer

INSART

format:Remotetype:Full-timecompany:Outsource

pythonfastapidjangoflaskreacttypescriptsqlpostgresqlgraphql

ai agentsprompt engineeringredux

englishB2

domainAI

> full description

Role Overview

We are looking for a Middle Full Stack Engineer to join our client’s team as soon as possible and contribute to the development of innovative, AI-powered solutions that help businesses optimize their go-to-market strategies. In this role, you will work across the full technology stack, collaborating with cross-functional teams to design, build, and enhance scalable products that drive business growth and deliver exceptional user experiences.

More information about us — [meet INSART]

Role Responsibilities

Design and build Python backend services: REST/GraphQL APIs, data models, integrations, background jobs.
Build and maintain the React.js front end for those services — component structure, state management, sensible UX.
Take features from ambiguous requirements to shipped, including the boring parts: tests, error handling, logging, docs.
Use AI coding agents to accelerate delivery, and take full ownership of what those agents produce — reviewing, correcting, and validating before it lands.
Participate in code review on both sides (human and AI-generated) and keep the codebase coherent.
Communicate clearly with the team and, where applicable, directly with clients.

Role Requirements

Python:

Strong command of modern Python: typing, async, packaging, the standard library, common pitfalls.
Solid with at least one major framework — FastAPI, Django, or Flask — and able to justify trade-offs.
Comfortable with relational data modeling, SQL, ORMs, and query performance basics.

React.js

Builds functional components with hooks; understands state, props, effects, and re-render behavior.
Comfortable with a typical modern toolchain (Vite/Next, TypeScript a strong plus, a state library like Pinia-equivalents/Redux/Zustand/Context).
Can integrate a front end against an API they also built, and debug across the boundary.

AI Engineering:

Context & prompt engineering for code. You know how to feed an agent the right context — project conventions (e.g. a well-maintained CLAUDE.md / rules file), specs, examples, constraints — so its output lands close to correct on the first pass instead of needing five rounds.
Decomposition for agents. You break work into chunks an agent can do well and that you can actually review, rather than throwing a vague mega-prompt at it and hoping.
Critical review of generated code. You treat AI output as a confident first draft, not truth. You catch hallucinated APIs, subtle logic errors, security issues, and “looks right but isn’t” code — and you can tell quickly when it’s faster to redirect the agent vs. write it yourself.
Knowing where AI helps and where it hurts. Good judgment on which tasks to delegate to an agent (boilerplate, scaffolding, refactors, test generation, exploration) and which to drive by hand (gnarly architecture decisions, security-critical paths, anything where being subtly wrong is expensive).
Velocity without quality drift. You maintain test discipline, review standards, and architectural coherence even when the tooling lets you generate code 5x faster. High output without a corresponding mess.
Strong communication skills: English B2+, Ukrainian — fluent.

Daily schedule

Our company supports work-life balance and allows you to tailor your schedule, which consists of 8 working hours and time for lunch. Shared business hours for most of our teams are 12 pm — 7 pm Kyiv time.

Interview Process