Senior AI Fullstack Engineer (Next.js & LLM)
New
100% remote (Poland)Full-TimeSenior
Salary5553 - 8330 USD per hour b2b currencySource=conversion; 4095 - 6143 GBP per hour b2b currencySource=conversion; 4345 - 6518 CHF per hour b2b currencySource=conversion; 4739 - 7108 EUR per hour b2b currencySource=conversion; 20160 - 30240 PLN per hour b2b currencySource=original
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Job Details
- Languages
- English C1
- Experience
- 8+ years of experience
- Required Skills
- Artificial IntelligenceTypeScriptNext.jsReactPrompt Engineering
Requirements
- 8+ years of experience as a consultant / forward deployed engineer
- Strong experience with Next.js (App Router), React, TypeScript
- Deep understanding of: Server vs Client Components (RSC), streaming, caching, revalidation, Server Actions
- Vercel AI SDK / LangGraph / MCP
- Experience building RAG systems
- Claude extended thinking / prompt caching / Batch APIs
- Proven experience shipping LLM-powered features to production
- Hands-on with Anthropic / OpenAI APIs (messages, tool use, streaming)
- Practical experience with: prompt engineering (structured output, few-shot, XML), tool calling / agent workflows, multi-turn orchestration
- Understanding of: token economics (input/output costs, context window), latency vs quality trade-offs
- Experience with: prompt evaluations (LLM-as-judge, rule-based), handling hallucinations and failure modes
- Ability to design robust AI systems, not just prototypes
- Strong ownership mindset
- Experience working directly with clients
- Clear communication and structured thinking (English C1)
- Ability to make decisions in ambiguous environments
Responsibilities
- Ship Production Apps: Build scalable web applications using Next.js (App Router) and TypeScript, ensuring high performance and clean architecture.
- Engineer AI Workflows: Develop and orchestrate LLM-powered features using Anthropic and OpenAI APIs, focusing on tool use and streaming.
- Agentic Orchestration: Design autonomous agent loops and multi-turn workflows, knowing when to use a structured pipeline versus a dynamic agent.
- Optimize & Evaluate: Manage token economics (pricing, context windows) and implement prompt evaluations (LLM-as-judge, rule-based) to ensure system reliability.
- Collaborate: Work directly with senior engineers, founders, and client teams to shape AI capabilities from concept to production.
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