Senior Full Stack TypeScript Engineer (AI)
New
K
KindgeekTax incentives
Fully remote: work from anywhere, Readiness to work roughly 11:00–20:00 Kyiv time; core collaboration hours of roughly 11:00–20:00 Kyiv timeFull-TimeSenior
SalaryA fixed rate plus KPI-based performance compensation
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Job Details
- Languages
- Fluent spoken English
- Experience
- 5+ years of commercial software engineering experience
- Required Skills
- Node.jsPostgreSQLTypeScriptNext.jsReactCI/CD
Requirements
- Have hands-on production experience with multi-agent or tool-calling architectures, such as agents that extract document data and hand it to other agents through explicit data contracts.
- Have 5+ years of commercial software engineering experience and real end-to-end ownership of production features.
- Have strong TypeScript and Node.js experience in production; candidates with a Python background are welcome if ready to work in a TypeScript codebase from day one.
- Have solid modern React and Next.js experience, including complex forms, server state, and caching.
- Have production PostgreSQL experience, including schema design, migrations on live data, history, and auditability.
- Have hands-on experience with queues, workflow engines, or event-driven systems, such as Inngest, Temporal, BullMQ, SQS, or Kafka.
- Have shipped at least one LLM-powered feature and be able to explain how it failed on real data and how the failure was contained without letting the system invent a value.
- Apply engineering discipline through regression-catching tests, observability, CI/CD, and careful verification of AI-generated code.
- Have a product mindset and be able to explain what a product does and for whom.
- Speak English fluently and be ready to work roughly 11:00–20:00 Kyiv time.
Responsibilities
- Own features end-to-end, from ambiguous business problems through data models, typed APIs, background workflows, and UI to stable production behavior.
- Build multi-agent document pipelines that extract data from client files and reliably hand it off to downstream agents.
- Design the boundary between probabilistic AI/ML output and the deterministic engine, including validation, provenance, and human review where needed.
- Integrate in-house ML predictions for scoring, estimation, and anomaly detection, and define product behavior when models are uncertain, wrong, or unavailable.
- Build durable, event-driven workflows and integrations that handle retries, idempotency, partial failure, and unreliable third-party services.
- Make AI behavior measurable through tracing, evaluation, and meaningful tests.
- Work with the CTO and product team to make trade-offs and risks explicit, share context, and document key decisions.
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