Jobs ML / AI

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. 

We are seeking a Senior AI Engineer to design, build, and scale enterprise-grade AI and Generative AI solutions. As part of a Business AI program, the team is building intelligent agents to streamline core enterprise processes and boost productivity. The goal is to free services professionals from repetitive tasks and accelerate time to value for customers. This role combines strong software engineering fundamentals with hands-on experience deploying LLM-powered systems into secure, production environments. You will drive initiatives from proof-of-concept through scalable enterprise deployment.

Details: 

Schedule: Full time remote 

Location: Europe-based 

Capacity: 100% (40 hours/week)
Language: English (mandatory), German (nice to have)

Responsibilities

AI Solution Development

Design, develop, and deploy enterprise AI and GenAI services

Guide solutions from PoC to secure production rollout

Build and integrate multi-agent AI systems and LLM-based products

Work with SAP data products and underlying data architectures

Manage ingestion, transformation, caching, and indexing workflows

Support distributed systems and big data processing environments

Implement CI/CD pipelines and MLOps best practices

Automate model training, validation, testing, and deployment

Work with Azure ML, Databricks, or AWS environments

Implement secure API design, secrets management, and access control

Contribute to security concept design

Ensure observability, reliability, and compliance in AI deployments

Collaborate with AI Product Owners, Data Scientists, and stakeholders

Create architecture diagrams, ADRs, and technical documentation

Ensure high-quality, well-documented codebases

Required Experience

7+ years of professional software engineering experience

Strong Python expertise (mandatory)

Experience with Node.js or Java (at least one additional language)

Backend framework experience (FastAPI, Flask, or Django)

Microservices architecture experience

Docker and Kubernetes experience

Experience with GitHub Actions, MLFlow, or similar orchestration tools

Hands-on ETL, API integration, and model deployment experience

Experience implementing CI/CD and MLOps in cloud environments

Knowledge of distributed systems and big data platforms

Experience working in Agile frameworks (Scrum, Kanban)

Fluent English and strong problem-solving mindset

Nice to Have

Experience with multi-agent or GenAI frameworks (LangChain, CrewAI)

Familiarity with SAP AI Core and SAP BTP

Experience with Jira (Scrum, SAFe)