[Hiring] Software Engineer – GenAI (LLM Applications) @Zeiss VisioGen

Role Description

This is a remote position.

We are looking for a passionate Software Engineer – GenAI to design and develop production-grade applications powered by Large Language Models (LLMs). In this role, you will work on Agentic AI workflows, Retrieval-Augmented Generation (RAG) systems, and intelligent patient-facing applications while collaborating with cross-functional teams to build scalable and reliable AI solutions.

Key Responsibilities

• GenAI Application Development
  • Design, develop, and deploy production-grade LLM-powered applications.
  • Build Agentic workflows and multi-step AI applications using frameworks such as LangChain and LangGraph.
  • Develop and maintain RESTful APIs and streaming services using FastAPI and asynchronous Python.
• RAG & AI Engineering
  • Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases and embedding models.
  • Support data ingestion, chunking, embedding, indexing, and retrieval workflows.
  • Optimize LLM performance for relevance, accuracy, safety, and response quality through prompt engineering and evaluation.
• Software Engineering & Collaboration
  • Write clean, scalable, and well-documented Python code following engineering best practices.
  • Contribute to CI/CD pipelines and deployment workflows across development, staging, and production environments.
  • Collaborate with Product, AI, and Engineering teams to design, build, test, and deploy AI solutions.
  • Troubleshoot technical issues and continuously explore emerging GenAI technologies to improve existing systems.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 2–3 years of software development experience, including at least 1 year building GenAI or LLM-based applications.
• Strong proficiency in Python, including asynchronous programming (async/await).
• Experience building APIs using FastAPI or similar Python frameworks.
• Good understanding of prompt engineering, Retrieval-Augmented Generation (RAG), and LLM application architecture.
• Experience with Git, version control, and CI/CD workflows.
• Strong analytical, problem-solving, and communication skills with the ability to work in a collaborative environment.

Preferred Qualifications

• Hands-on experience with LangChain, LangGraph, or similar LLM frameworks.
• Experience with vector databases such as Pinecone, Weaviate, pgvector, Chroma, or FAISS.
• Familiarity with Azure Pipelines, GitHub Actions, or Jenkins.
• Experience deploying applications on Azure, AWS, or GCP.
• Working knowledge of Docker and containerized applications.
• Experience with PostgreSQL, MySQL, MongoDB, Redis, or similar databases.
• Portfolio or GitHub projects demonstrating software engineering and GenAI development expertise.