Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from RIIM
*]:pointer-events-auto R6Vx5W_threadScrollVars scroll-mb-[calc(var(--scroll-root-safe-area-inset-bottom,0px)+var(--thread-response-height))] scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))] dir=auto data-turn-id=request-WEB:0fda52b1-29ea-4a88-a19e-167fb555f60e-8 data-turn-id-container=request-WEB:0fda52b1-29ea-4a88-a19e-167fb555f60e-8 data-testid=conversation-turn-16 data-scroll-anchor=false data-turn=assistant>Job Summary
We are looking for an experienced Generative AI Engineer with 8–10 years of overall software engineering experience and strong expertise in Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), Prompt Engineering, and scalable AI application development. The candidate will design, develop, and deploy enterprise-grade Gen AI solutions using modern AI frameworks and cloud platforms.
Key Responsibilities
- Design and develop enterprise Generative AI solutions using OpenAI, Claude, Gemini, Llama, Mistral, or Hugging Face models.
- Build and optimize RAG pipelines using vector databases such as Pinecone, FAISS, ChromaDB, Weaviate, or Milvus.
- Develop Agentic AI workflows using LangChain, LangGraph, CrewAI, AutoGen, or LlamaIndex.
- Fine-tune, evaluate, and deploy LLMs for business use cases.
- Integrate AI models with enterprise applications through APIs and microservices.
- Develop scalable backend services using Python, FastAPI, Flask, or Node.js.
- Implement prompt engineering, model evaluation, guardrails, and AI safety practices.
- Work with structured and unstructured data pipelines for AI applications.
- Deploy AI applications on AWS, Azure, or Google Cloud Platform environments.
Required Skills
- Strong programming experience in Python OR Java.
- Hands-on experience with LLMs and Generative AI frameworks.
- Experience with:
- LangChain / LangGraph
- RAG Architecture
- Prompt Engineering
- REST APIs & Microservices
- Knowledge of NLP, Transformers, embeddings, and fine-tuning concepts.
- Experience with Docker, Kubernetes, CI/CD, and MLOps.
- Strong cloud experience in AWS, Azure, or Google Cloud Platform.
- Experience with SQL/NoSQL databases.
- Understanding of AI governance, security, and responsible AI practices.
Education
- Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field.
Nice-to-Have Technologies
- Hugging Face
- PyTorch / TensorFlow
- DSPy
- LangSmith
- Neo4j Knowledge Graphs
Source: RIIM careers