ROKO Labs is a fast-growing strategic product and technology consultancy based in NYC. We are seeking a highly motivated and resourceful person who enjoys solving complex problems! We have a great track record of working with large Fortune 500 companies and VC-backed start-ups. We are incredibly proud of our work and would be excited to share it with you! Our clients value that we understand their businesses and help to build products that users love! Additionally, our extended team spans multiple countries, making for fun cultural exchanges.
ROKO Labs is looking for a Senior Python Engineer with deep AI expertise to join our team working on large-scale, production-grade intelligent systems. If you love writing clean, well-tested Python code, thrive in cross-functional environments, and are excited about building real-world AI solutions — come join a team of like-minded, caring professionals.
You will be a core technical contributor on complex AI-powered projects, combining strong Python engineering fundamentals with hands-on experience in modern AI/ML technologies. You'll work closely with Product Owners, customers, engineering, and data teams to translate requirements into robust, scalable systems — and take real ownership of technical decisions.
Design and implement end-to-end Retrieval-Augmented Generation (RAG) pipelines, embedding workflows, and semantic search solutions in Python
Build, optimize, and maintain data ingestion pipelines and background task processing using Celery, RabbitMQ, or Kafka
Integrate and manage LLM APIs and AI platforms (e.g., OpenAI, Anthropic, Azure OpenAI) within robust Python service architectures
Design and optimize database schemas and queries across relational (PostgreSQL, MySQL) and NoSQL (MongoDB, DynamoDB) databases
Design scalable vector database architectures (e.g., Pinecone, Weaviate) to support AI-driven search and retrieval features
Containerize and orchestrate Python services using Docker and Kubernetes for reliable, repeatable cloud deployments (AWS, Azure, or GCP)
Identify and resolve performance bottlenecks in Python applications through profiling, caching strategies, and code optimization
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