1168 Senior AI Developer

Intetics · Poland (Remote) · posted Sep 30, 2026

Open to candidates in Poland

senior
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What this role actually asks for

Extracted by RemoteHunt

Must have

  • •6+ years overall IT experience
  • •Production experience with LLM agents
  • •Experience with agent frameworks
  • •Production-grade RAG and memory engineering
  • •Experience with agentic patterns
  • •Experience with LLM evaluation and monitoring
  • •Experience with Docker and CI/CD

Nice to have

  • •Experience in fintech or trading
  • •Background in regulated industries
  • •Broader AWS or Azure cloud expertise
  • •Experience with LLM evaluation platforms

Tools and technologies

LLMRAGAgentic AIPythonAmazon BedrockMicrosoft FoundryAzure AI FoundryAzure OpenAILangGraphLangChainLlamaIndexSemantic KernelAutoGenStrands AgentsOpenAI Agents SDK

The full posting

Intetics Inc. , a leading American technology company specializing in custom software application development, distributed professional teams creation, software product quality assessment, and "all-things-digital" solutions, is looking for an AI Developer (LLM / RAG / Agentic AI) to join its innovative team.

Project Responsibilities

Design, build, and maintain LLM-based agents in production environments, both customer-facing and internal. Build MCP servers on top of existing databases and production systems, and orchestrate multiple internal and external MCP servers under a unified agent framework. Design and implement memory, context management, and RAG architectures for production use. Establish evaluation frameworks, handle edge cases, and continuously improve agent performance after release. Work within architectures that combine databases, APIs, interfaces, agents, and orchestration applications. Develop AI solutions using Amazon Bedrock and/or Microsoft Foundry. Collaborate with cross-functional teams to deliver scalable and reliable AI-powered products.

Candidate's Portrait

We are looking for a hands-on AI Engineer (Middle+ to Senior level) who has successfully delivered AI agents into production and can clearly explain implementation challenges, failure cases, and optimization approaches. The ideal candidate is passionate about AI, actively explores new tools and models, and has a proven track record building intelligent systems beyond experimentation. 1.5-2+ years of hands-on experience with LLMs and AI agents in production environments. Strong background in Machine Learning, Python development, or Data Science. Self-driven, innovative, and continuously learning emerging AI technologies.

Must-Haves

6+ years of overall experience in IT as a Software Engineer, ML Engineer, or AI Engineer. Hands-on production experience with Amazon Bedrock and/or Microsoft Foundry (Azure AI Foundry, Azure OpenAI). Proven experience building and deploying LLM-based agents to production, including customer-facing conversational AI and internal workflow automation agents. Strong experience with at least one agent framework: LangGraph, LangChain, LlamaIndex, Semantic Kernel, AutoGen, Strands Agents, or OpenAI Agents SDK . Deep MCP expertise, including building MCP servers on top of existing databases and systems, integrating external MCP servers, and orchestrating multiple MCP services under a single agent. Strong experience with production-grade RAG, memory, and context engineering, including:

  • Embeddings
  • Chunking strategies
  • Hybrid search
  • Reranking
  • Vector databases
  • Short-term and long-term agent memory

Practical experience implementing agentic patterns such as:

  • ReAct
  • Planner-Executor
  • Reflection
  • Router
  • Supervisor
  • Multi-Agent Systems
  • Human-in-the-Loop

Experience with LLM evaluation, guardrails, monitoring, and iterative optimization based on production usage and failure analysis. Strong understanding of system architecture involving databases, APIs, agents, and orchestration applications. Hands-on experience with Docker and CI/CD pipelines.

Nice-to-Have

Experience in fintech, trading, investing, brokerage, or cryptocurrency-related products. Background in regulated industries with strong requirements around compliance, data protection, and AI output auditability. Broader AWS or Azure cloud expertise beyond AI services. Experience with LLM evaluation and observability platforms such as LangSmith, Langfuse, Ragas , or custom evaluation pipelines. Advanced practical expertise with modern agentic AI development tools and rapid prototyping approaches.

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