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Senior Developer - GenAI
Java

Senior Developer - GenAI

Type of work
Full-time
Experience
Senior
Employment Type
B2B
Operating mode
Hybrid

Tech stack

    English

    B2

    GenAI

    advanced

    LLM

    advanced

    AWS

    regular

    Python

    regular

    rag

    regular

Job description

Online interview

🌍 Join Us

Be part of a team that's transforming how businesses operate with AI. If you're passionate about building impactful products and advancing the future of work, we want to hear from you.


🚀Senior Developer – GenAI

Location: Warsaw, Poland (Hybrid 2 days / week)

💼 Role Overview

As a Senior Software Engineer on the ChatGPT for Work team, you will:

  1. Architect & Build: Design and implement backend systems supporting Generative AI workflows and services.
  2. Develop Microservices: Create APIs integrating GenAI models, vector databases, and orchestration tools like LangChain and LangGraph.
  3. Optimize Infrastructure: Build scalable systems for deploying and serving LLMs and AI pipelines in production.
  4. Maintain Data Pipelines: Support GenAI use cases, including prompt data processing and model feedback loops.
  5. Collaborate Across Teams: Work with AI/ML engineers to enable plug-and-play components in agentic workflows.
  6. Enhance Performance: Debug, profile, and optimize GenAI applications, including prompt execution paths and model inference.
  7. Document Systems: Write technical documentation related to GenAI service design, deployment procedures, and best practices.


🧠 Required Skills

  1. GenAI Expertise: Hands-on experience with LLMs, prompt engineering, embeddings, fine-tuning, or building RAG pipelines.
  2. Programming Languages: Proficiency in Python, Java, or Scala.
  3. Backend Engineering: Experience with microservices, REST APIs, Kafka, and cloud platforms (AWS/Azure).
  4. Development Tools: Familiarity with Docker, Kubernetes, CI/CD, and Git.
  5. System Design: Strong foundation in software design principles, testing, and version control.


🎯 Desired Skills

  1. AI Toolchains: Exposure to prompt engineering, embeddings, or AI-based toolchains.
  2. Agentic AI Systems: Experience in building or integrating with LLMs (e.g., OpenAI, Claude), use of tools like LangChain, LangGraph, Copilot, or vector DBs.

Startup Experience: Experience as a startup founder or early-stage engineer is a plus.