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Design and deploy production-grade LLM applications using Agentic workflows and RAG systems. Develop RESTful APIs and collaborate with cross-functional teams to build scalable AI solutions for healthcare.
This is a remote position.
Role: Software Engineer – GenAI (LLM Applications)
Location: India (Remote / Hybrid)
Experience: 2–3 Years
Employment Type: Third-Party Payroll
About ZEISS VisioGen
ZEISS VisioGen is building the future of AI-powered healthcare by developing human-verified clinical communication solutions for ophthalmology practices. We combine cutting-edge Generative AI with clinical expertise to build scalable, production-ready applications that enhance patient engagement and improve healthcare delivery.
Role Overview
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.
What We're Looking For
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.
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