Job VC
Senior AI Engineer
About ChatRevenue.ai
ChatRevenue.ai was founded by Ratmir Timashev (founder of Veeam) and Vlad Voskresensky (founder of Revenue Grid).
We are building an agentic sales automation for post-CRM era. The AI-native product combines structured and unstructured data, LLM workflows, and agentic automation to help sales people to focus properly, work more efficiently and automate repetitive sales processes.
The product is already being tested by early customers. We are growing the core engineering team and looking for people who want to work on real product systems with direct impact on architecture, quality, and speed of delivery.
About the role
We are looking for a Senior Generative AI Engineer with 5+ years of commercial Python experience and hands-on experience building production GenAI / RAG systems.
This is a hands-on engineering role focused on:
Python backend
LLMs and RAG
AI Copilot / assistant workflows
We are looking for someone who can take a problem, propose a practical solution, and move it to production.
What you will do
Design, build, deploy, and maintain production GenAI / RAG pipelines
Integrate LLMs and agentic assistants into product workflows
Improve latency, reliability, scalability, and cost-efficiency of AI systems
Evaluate and implement new GenAI, multi-agent, and orchestration frameworks
Contribute to architecture and technical decisions across the platform
What we are looking for
5+ years of commercial Python experience
Strong backend experience with FastAPI, APIs, webhooks, Docker, Kubernetes, Git, and CI/CD
Commercial experience with LLMs in production
Strong hands-on experience with RAG, retrieval workflows, embeddings, and vector search
Experience with LangChain, LangGraph, LangSmith, or similar frameworks
Good knowledge of SQL, Pandas, ETL, data cleaning, and ingestion pipelines
English: B2 or higher
High ownership, independence, and product mindset
Nice to have
Multi-agent LLM systems
Knowledge graphs, graph databases, or graph-based retrieval
Kafka, Azure Event Hub, or other event-driven systems
Azure cloud infrastructure
Production ML / NLP systems
Evaluation, tracing, observability, and optimization of AI pipelines
Graph algorithms or tools like NetworkX
What we offer
Remote-first setup
Flexible schedule aligned with European time zones
A core engineering role in an AI-native product
Direct influence on technical decisions and architecture
Real ownership and visible product impact
If you have strong Python backend fundamentals and real production GenAI / RAG experience, we’d love to talk.