About this role
Celonis is the global leader in Process Intelligence and the pioneer of Process Mining technology. As one of the world’s fastest-growing enterprise SaaS companies, we are changemakers pushing the boundaries of what’s possible. We invest heavily in advanced AI capabilities—specifically our Process Intelligence Graph—to turn data insights into immediate business action. We believe there is a massive opportunity to unlock global productivity and sustainability by placing intelligence at the core of every business process. Join our mission to make processes work for people, companies, and the planet.
Overview
You will join the Sailfin Accounts Receivable (AR) Team , a product engineering team working in the Finance and Accounting domain. The team designs, develops, deploys, and maintains a large-scale AR product used by global customers. Most of the team is based in India, including this role in Bangalore , and we work with a modern technology stack —AI/ML models, LLMs, multi-agent systems, cloud platforms, and automation frameworks. Our focus is on building secure, scalable, and intelligent solutions that transform financial operations.
The Role
We are looking for an Applied AI Engineer who can build production-ready predictive, generative, and agentic AI solutions for the Finance domain.
You will handle end-to-end development—from identifying use cases to deploying AI features in production. You must have experience building real-world, production-grade AI and agentic systems , not just POCs.
Responsibilities
• Partner with product owners and finance experts to identify strong AI use cases in Accounts Receivable.
• Design and build predictive models, generative AI features, and multi-agent systems tailored to business problems.
• Develop LLM-based copilots and autonomous agents , including human-in-loop flows, security guardrails, and audit trails.
• Work closely with software engineers and data scientists to embed AI features into the product.
• Build and maintain secure, scalable MLOps pipelines for training, deployment, and monitoring.
• Continuously evaluate and improve model performance and user impact.
• Stay current with the latest advancements in LLMs, NLP, multi-agent frameworks, and applied AI engineering.
• Set up and tailor AI demos as needed for customers, stakeholders, and internal teams.
• Contribute to a culture of innovation, collaboration, and continuous learning.
Required Experience
AI/ML/LLM Experience
• 4+ years of AI/ML engineering experience.
• 3+ years of hands-on experience with LLM-based solutions .
• 1+ year of experience building agentic systems (production-ready, not POCs).
Multi-Agent & Autonomous Systems
• Strong understanding of multi-agent architectures , memory systems, tool-use, orchestration, routing, and safety guardrails.
• Experience building autonomous or semi-autonomous agents with governance, logging, and human-in-loop flows.
Technical Skills
• Strong programming skills i