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Senior AI Engineer with LangGraph

  • Ałmaty
  • Astana
  • Belgrad
  • Charków
  • Dnipro
  • Erywań
  • Kijów
  • Kluż-Napoka
  • Kraków
  • Larnaka
  • Łódź
  • Lublin
  • Lwów
  • Odesa
  • Remote.Bulgaria
  • Remote.Georgia
  • Remote.Kazakhstan
  • Remote.Poland
  • Ryga
  • Sofia
  • Tbilisi
  • Warna
  • Warszawa
  • Wrocław
Mały zespół (1-10 osób)

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Project overview

You will contribute to building a production-grade conversational AI platform designed for a multi-tenant SaaS environment. The platform focuses on delivering reliable, scalable, and observable AI-driven interactions, transforming complex user inputs into structured and actionable outputs for real users.

Team

You will collaborate with a cross-functional team of AI engineers, backend engineers, and Product Managers. The team works in a highly collaborative environment with shared ownership of production systems and a strong focus on continuous improvement and data-driven decision-making.

Position overview

We are looking for a Senior AI Engineer to design and build production-grade conversational AI systems in a multi-tenant SaaS environment. You will own end-to-end AI solutions, focusing on prompt pipelines, structured outputs, evaluation frameworks, and production reliability while ensuring high-quality AI experiences at scale. This role requires hands-on experience shipping production LLM systems to real users, not only building prototypes or proof-of-concept solutions.

Technology stack

AWS, LangGraph, LangChain, OpenAI, Amazon Bedrock AgentCore, MCP, Arize, LangSmith, Braintrust, A2A protocols

Responsibilities

  • Design, build, and maintain production conversational AI systems operating in a multi-tenant SaaS environment
  • Develop and optimize prompt pipelines and structured output workflows to ensure reliability and consistency
  • Design end-to-end AI solutions from requirements gathering through deployment and production support
  • Build and maintain evaluation frameworks including deterministic, online, and LLM-as-a-judge approaches
  • Implement observability pipelines including tracing, latency monitoring, token tracking and prompt and output logging
  • Monitor production systems and continuously improve quality, latency, safety, and operational efficiency using evaluation and observability data
  • Collaborate with Product Managers and engineering teams to define requirements and deliver production-ready AI solutions
  • Drive architectural decisions and evaluate trade-offs to improve system scalability and maintainability
  • Independently propose technical approaches, refine requirements with Product Managers, and execute with limited supervision

Requirements

  • Proven experience building production LLM systems used by real customers
  • Ability to clearly describe a specific production AI or conversational system personally built and delivered
  • Experience designing AI systems end to end and delivering production-ready applications
  • Strong experience developing conversational AI applications
  • Understanding of prompt engineering, structured outputs, and completion logic
  • Experience implementing production observability including tracing, latency monitoring, token tracking, and logging pipelines
  • Experience building evaluation frameworks including deterministic evaluations, online evaluations, and LLM-as-a-judge methodologies
  • Experience measuring regressions and making engineering decisions based on evaluation results
  • Experience improving structured output reliability in production systems under real latency constraints
  • Hands-on experience with LangGraph or LangChain
  • Experience working with production AI workloads in AWS with focus on scalability, reliability, and cost optimization
  • Ability to drive technical decisions, evaluate trade-offs, and collaborate with Product Managers to refine requirements
  • English working proficiency

Nice to have

  • Experience with Voice AI technologies including speech-to-text and text-to-speech
  • Experience building real-time conversational agents and turn-detection systems
  • Familiarity with vision-language models
  • Experience with Amazon Bedrock AgentCore and OpenAI APIs
  • Experience working with MCP and A2A communication protocols
  • Familiarity with observability tools such as Arize, LangSmith, or Braintrust

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