Job Title: Senior Generative AI Engineer (Drafting & RAG Systems)Role OverviewWe are looking for a Senior Generative AI Engineer to lead the development and deployment of our next-generation Automated Drafting Tool. You will be responsible for the entire lifecycle of the AI features—from local prototyping using Ollama to scaling globally via OpenAI APIs.The ideal candidate has a /"Full-Stack AI/" mindset: you understand how to retrieve context using RAG, manage high-dimensional data in Vector Databases, and ensure the final drafted output is coherent, accurate, and contextually aware.Key Responsibilities1. AI Architecture & Drafting LogicDesign and implement end-to-end Retrieval-Augmented Generation (RAG) pipelines specifically optimized for document drafting.Develop advanced Prompt Engineering strategies to handle complex drafting constraints (tone, legal/technical compliance, and formatting).Implement hybrid model strategies, utilizing Ollama for local development, testing, and privacy-sensitive tasks, while orchestrating OpenAI (GPT-4o/o1) for production-level reasoning.2. Data & Vector EngineeringBuild and maintain scalable Vector Databases (e.g., Pinecone, Weaviate, Milvus, or FAISS).Optimize document ingestion pipelines: chunking strategies, embedding model selection, and metadata filtering to improve retrieval precision.Implement /"Agentic RAG/" where the system can self-correct or multi-step reason through a draft.3. Deployment & MLOps (Local to Cloud)Bridge the gap between local ideation (running models on Ollama/Local GPUs) and cloud production environments.Deploy AI services using containerization (Docker/Kubernetes) and manage API latency, rate limits, and token costs.Establish monitoring for AI performance, including hallucination detection and /"groundedness/" metrics.Required Skills & QualificationsMandatory ExperienceExperience: 3+ years of professional experience in AI/Machine Learning or Backend Engineering with a heavy GenAI focus.LLM Orchestration: Deep hands-on experience with LangChain or LlamaIndex.Model Proficiency: Expert knowledge of the OpenAI API ecosystem and local model runners like Ollama.Vector Expertise: Proven track record of implementing and optimizing Vector Databases and RAG workflows.Programming: Mastery of Python (FastAPI/Flask) and asynchronous programmingJIRA + Confluence exposure is must haveTechnical StackModels: OpenAI (GPT-4), Ollama (Llama 3, Mistral, Mixtral).Tools: LangChain, LlamaIndex, LangSmith (for tracing).Database: Pinecone, ChromaDB, or pgvector.Infrastructure: Docker, AWS/GCP/Azure, GitHub Actions for CI/CD.What We Look For (The /"Hacker/" Mindset)Production Proven: You have moved at least one GenAI product from a Jupyter Notebook/Local Script to a live environment with real users.Problem Solver: You know how to handle the /"stochastic/" nature of LLMs and can build guardrails to prevent hallucinations in drafting.Architecture First: You care about token optimization and latency just as much as you care about the quality of the text generated.
Job Title
Senior Generative AI Engineer